Source: http://patents.com/us-9633537.html
Timestamp: 2018-10-20 17:25:01
Document Index: 185943198

Matched Legal Cases: ['art\n2007', 'Application No. 2', 'Application No. 11754563', 'Application No. 11754563', 'Application No. 2', 'Application No. 14002757', 'Application No. 14002757', 'Application No. 14003506', 'Application No. 14003505', 'Application No. 14003504', 'Application No. 14003506', 'Application No. 14003505', 'Application No. 14003504', 'Application No. 14003504', 'Application No. 14003505', 'Application No. 14003506', 'Application No. 14003505', 'Application No. 14003504']

US Patent # 9,633,537. Methods and apparatus to detect and warn proximate entities of interest - Patents.com
United States Patent 9,633,537
Beggs , et al. April 25, 2017
Systems and methods to detect and warn proximate entities of interest are described herein. An example method includes determining threat levels for hazards in a plurality of different zones within a building, classifying the threat levels into at least one of a first threat level and a second threat level, designating a first zone of the plurality of different zones having the first threat level with a first detectable indicator, and designating a second zone having the second threat level with a second detectable indicator.
Beggs; Ryan P. (Dubuque, IA), Boerger; James C. (Franksville, WI), Hoffmann; David J. (Peosta, IA), Markham; Ken (Lee's Summit, MO), McNeill; Matthew (Whitefish Bay, WI), Muhl; Timothy (Slinger, WI), Nelson; Kyle (Cedarburg, WI), Oates; James (Mequon, WI), Senfleben; Jason (Milwaukee, WI)
Beggs; Ryan P.
Boerger; James C.
Markham; Ken
McNeill; Matthew
Muhl; Timothy
Nelson; Kyle
Oates; James
Family ID: 1000002547010
14/610,820
US 20150170498 A1 Jun 18, 2015
12844295 Jul 27, 2010 9230419
Current CPC Class: G08B 21/02 (20130101); B60Q 1/26 (20130101); B60Q 1/2673 (20130101); B60Q 1/50 (20130101); B60Q 1/525 (20130101); B60Q 9/008 (20130101); B66F 17/003 (20130101); G08B 5/36 (20130101); G08B 6/00 (20130101); G08B 21/18 (20130101); G08G 1/005 (20130101); G08G 1/166 (20130101); B60Q 2400/50 (20130101)
Current International Class: G08B 21/00 (20060101); G08B 21/18 (20060101); G08B 5/36 (20060101); G08B 6/00 (20060101); B60Q 1/50 (20060101); G08G 1/16 (20060101); G08G 1/005 (20060101); B66F 17/00 (20060101); B60Q 9/00 (20060101); B60Q 1/52 (20060101); G08B 21/02 (20060101); B60Q 1/26 (20060101)
Field of Search: ;340/691.1,691.6,686.6,435,6.11,540,541,686.1,461,438,425.5,463,995.25
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1. A method comprising: receiving a classification of predetermined threat levels of different zones within a building, the predetermined threat levels to include at least one of a first predetermined threat level and a second predetermined threat level; associating a first detectable indicator with a first zone of a plurality of different zones having the first predetermined threat level; associating a second detectable indicator with a second zone of the plurality of different zones having the second predetermined threat level; and providing a vehicle capable of moving between the first and second zones, the vehicle capable of detecting, via a detector, at least one of the first detectable indicator or second detectable indicator.
2. The method of claim 1, further comprising providing at least one of the first detectable indicator or the second detectable indicator as a color.
3. The method of claim 2, wherein providing at least one of the first detectable indicator or the second detectable indicator as a color comprises coloring at least one of a flooring of the first zone having the first predetermined threat level with a first color or coloring a flooring of the second zone having the second predetermined threat level with a second color, the first color being different than the second color.
4. The method of claim 2, wherein providing at least one of the first detectable indicator or the second detectable indicator as the color comprises using color lighting associated with at least one of the first zone having the first predetermined threat level or the second zone having the second predetermined threat level.
5. The method of claim 1, further comprising detecting the first detectable indicator which is at least one of a first colored floor or a first colored light indicative of the first zone, or detecting the second detectable indicator which is as at least one of a second colored floor or a second colored light indicative of the second zone.
6. The method of claim of claim 1, further comprising modifying an operational parameter of the vehicle upon detection of at least one of the first detectable indicator or the second detectable indicator.
7. The method of claim 6, wherein modifying the operational parameter of the vehicle comprises at least one of limiting the vehicle to a first speed when the first detectable indicator is detected or limiting the vehicle to a second speed when the second detectable indicator is detected, the first speed being different than the second speed.
8. A method for detection of hazards in different areas of a building, the method comprising: assigning a first predetermined threat level for a hazard in a first area of the different areas of the building; assigning a second predetermined threat level for a hazard in a second area of the different areas of the building, the first predetermined threat level being different than the second predetermined threat level; employing a first detection system to detect the hazard in the first area assigned the first predetermined threat level, the first detection system having a first ability to detect the hazard in the first area; modifying, via the first detection system, an operational parameter of a vehicle based on the vehicle being in the first area and employing a second detection system to detect the hazard in the second area assigned the second predetermined threat level, the second detection system having a second ability to detect the hazard in the second area, the first ability being different than the second ability.
9. The method of claim 8, wherein modifying the operational parameter of the vehicle comprises limiting a speed of the vehicle in the first area.
10. The method of claim 8, wherein employing the first detection system comprises monitoring, via the first detection system, the hazard in the first area.
11. The method of claim 8, wherein employing the second detection system comprises monitoring, via the second detection system, the hazard in the second area.
12. The method of claim 8, further comprising assigning a first color to the first area having the first threat level and assigning a second color to the second area having the second threat level, the first color being different than the second color.
13. The method of claim 12, further comprising distinguishing between the first color and the second color via at least one of the first detection system or the second detection system.
14. The method of claim 8, further comprising adjusting the first predetermined threat level for the hazard in the first area of the different areas based on a dynamic characteristic of the first area.
15. A method for detection of hazards in different areas of a building, the method comprising: assigning a first predetermined threat level for a hazard in a first area of the different areas of the building; assigning a second predetermined threat level for a hazard in a second area of the different areas of the building, the first predetermined threat level being different than the second predetermined threat level; employing a first detection system to detect the hazard in the first area assigned the first predetermined threat level, the first detection system having a first ability to detect the hazard in the first area; employing a second detection system to detect the hazard in the second area assigned the second predetermined threat level, the second detection system having a second ability to detect the hazard in the second area, the first ability being different than the second ability; and adjusting the first predetermined threat level for the hazard in the first area of the different areas based on a dynamic characteristic of the first area, wherein adjusting the dynamic characteristic is based on at least one of a population density, traffic density or a temporal characteristic in the first area.
16. The method of claim 15, further comprising capturing the dynamic characteristic based on statistical analysis.
17. The method of claim 16, wherein statistical analysis comprises monitoring the first area over a predefined period of time using at least one of a population density or a traffic density of the first area.
18. The method of claim 17, wherein monitoring the first area further comprises monitoring the first area over a time-based period such as at least one or more workshifts to determine at least one of the population density or the traffic density of the first area.
19. A method for detection of hazards in different areas of a building, the method comprising: assigning a first threat level for a hazard in a first area of the different areas; assigning a second threat level for a hazard in a second area of the different areas, the first threat level being different than the second threat level; employing a first detection system to detect the hazard in the first area assigned the first threat level, the first detection system having a first ability to detect the hazard in the first area; and employing a second detection system to detect the hazard in the second area assigned the second threat level, the second detection system having a second ability to detect the hazard in the second area, the first ability being different than the second ability; adjusting the first threat level for the hazard in the first area of the different areas based on a dynamic characteristic of the first area, wherein adjusting the dynamic characteristic is based on at least one of a population density, traffic density or a temporal characteristic in the first area.
20. The method of claim 19, further comprising capturing the dynamic characteristic based on statistical analysis.
21. The method of claim 20, wherein statistical analysis comprises monitoring the first area over a predefined period of time using at least one of a population density or a traffic density of the first area.
22. The method of claim 21, wherein monitoring the first area further comprises monitoring the first area over a time-based period such as at least one or more workshifts to determine at least one of the population density or the traffic density of the first area.
Several factors can increase the likelihood of such accidents occurring. One factor is the crowded, busy, noisy, distracting environment referred to above. The presence of such distractions can prevent an endangered individual from realizing and reacting to a dangerous situation. Ironically, one source of such distractions are the myriad lights, strobes, horns and/or buzzers intended to warn against such dangers. Another factor is the presence of blind spots. An individual walking down an aisle in such a facility is not able to see potential dangers around the corner at the end of the aisle, or at a mid-aisle break. The way forktrucks are used to load and unload trucks parked at a loading dock also create blind spots for a driver of the forktruck. Typically, a fork truck is driven forward into a trailer, and then driven in reverse to depart the trailer. While swiveling seats and/or fork truck mounted mirrors are used in attempts to minimize this problem, these attempted solutions are not completely satisfactory. Indeed, an individual that spends any significant amount of time in such a facility typically adopts the practice of stopping and looking into each trailer parked at a loading dock as he traverses from dock to dock--for fear of being struck by an inattentive or blind-spotted backing fork truck.
The current mechanisms for preventing or minimizing the severity of these kinds of accidents generally fall into two categories. The first category is personal safety items--typically some sort of apparel. Common examples include hard hats, safety glasses, steel-toed shoes or boots and safety vests. Most of these apparel items are intended to minimize the effect of such an accident. A hard hat, for example, can cushion but not prevent a blow to the head. Some safety vests are intended to help in preventing accidents, as they can be made of highly reflective or brightly-colored fluorescent material to increase the visibility of the wearer so they can be seen by a fork truck driver or other source of hazard. In general, these safety items are limited in their effectiveness in that they are passive. On the other hand, they do provide the benefit of being worn by and traveling with the person being protected.
Systems also exist to attempt to warn either pedestrians or proximate fork trucks of imminent collisions between the two. While a variety of sensing technologies have been coupled with warning signaling, such systems do not fully or effectively address the situation. For example, the warnings they provide may suffer from a lack of specificity. This lack of specificity may be in regard to what the hazard is. A given facility can have so many lights, horns and sirens that it may be difficult for an endangered individual to properly associate a given warning with a given threat. The lack of specificity may also relate to who is in danger. If, for example, a sensing system is intended to detect when a person has entered into a large, designated area, several people in close proximity to the area may hear or see a warning and may all be under apprehension of danger based on that warning signal, even though only one of them has actually breached the area. Given this example, a more likely result is that all of the individuals will ignore the warning as it is unable to specify who is in danger. The lack of specificity may also apply to the location, direction, or distance (in either physical distance or temporal distance) of the impending hazard. Relatedly, the timing of the hazard may be imprecisely conveyed by the warning used--with the endangered individual not knowing if there is a generalized threat that may occur at any time, or if a given threatened harm is imminent. This unduly limits the opportunity for the threatened individual to take appropriate avoiding or remedial action relative to the threat. Additionally, an imprecise and/or constant apprehension of danger may result in the loss of productivity of the affected personnel.
A first category of sensing systems to detect or sense potentially dangerous interactions between forktrucks and pedestrians (or other vehicles, people or equipment in a facility) uses detection or sensing techniques based on proximity. In general, the sensing technology detects and/or determines when a potentially dangerous condition exists based on the proximity of, for example, a potentially harmed entity (a pedestrian) and a dangerous instrumentality (e.g. a blind intersection, or a forktruck). As used herein, such potentially dangerous (or dangerous in fact) situations will be referred to collectively as "threats". For example, a sensing system can determine threats at a fixed location such as a blind intersection. A first example system uses two ultrasonic sensors located at a corner--one orientated in a first direction or "field of range" of an approach, and the other orientated in a second direction or field of range different from the first direction or field of range. When the system detects bodies or entities of interest on both fields of range, a generalized warning is given. The detection is based on the time delay between sending the ultrasonic signal and receiving the reflected signal from a body. In another example, a system includes a sensing apparatus mounted above an intersection to scan or look down the aisles approaching the intersection (e.g., four aisles, three aisles, etc). Detection of an approaching object that is large enough (i.e. not pedestrians) causes a warning. The system can discriminate between approaching and retreating objects. Another example system uses photoeyes mounted near potentially dangerous locations in combination with reflectors or reflective tape on the forktruck. Passage of the forktruck triggers the photoeye indicating proximity of the forktruck to the potentially dangerous location and triggers general warnings. However, the current array of generalized warning and threat-communication systems have limited utility in this critical function of preventing or minimizing these potentially very hazardous industrial accidents. In these cases, of course, the warning is only generalized, and indicative of a potentially dangerous condition. Even so, such systems could have some application to more effective threat detection and communication. For example, a particularly dangerous area is the area surrounding a dock leveler when a truck is being loaded or unloaded, since forktrucks departing the truck are traveling in reverse or backward, and the operator may not have adequate sight lines to see pedestrians in the area. A system capable of determining that 1) a forktruck is in the trailer (or even leaving the trailer if a directionally-discriminatory system is used) is combined with a means for determining the presence or approach of a pedestrian to the dangerous area around the leveler to trigger a warning. This warning is specific in terms of indicating that a forktruck is coming out of the trailer. Additionally and alternatively, the warning is personally directed to the person approaching harms way. Such solutions are disclosed in a co-pending US Patent Application, Publication Number 2008/0127435, which is incorporated herein by reference in its entirety.
In another example, a magnetic field is generated by a field generator on a hazardous mobile machine, and pedestrians carry detectors for detecting the presence and strength of that field. This system has the benefit of both the transmitters and receivers being wire loops that can create magnetic fields for applied current, or detect magnetic fields to generate detectable current. An example use of RF signals includes both pedestrians and the dangerous instrumentality having transceivers. Further, a signal processing unit on the hazardous mobile machine determines the distance of a pedestrian (in one of three ranges based on signal strength) and is in communication with a control unit that controls certain hazardous aspects of machine operation based on the proximity of the pedestrian relative to the machine. Such functionality could apply to the systems of this disclosure, in those aspects of forktruck operation could be controlled based on data about the proximity of pedestrian or other hazards relative to the hazardous mobile machine. This could be particularly beneficial in the context of potential collisions occurring around "blind corners"--since an area-generalized warning might not reach the affected pedestrian--slowing or stopping the forktruck for a perceived hazard could be beneficial. Another RF based system uses a tuned optical transmitter to create a cone-shaped warning zone below a moving hazard. Another system uses an RF signal on the dangerous equipment to send an interrogation signal. Any pedestrian receivers in appropriate range (based, for example on signal strength) send back their identification (ID) associated with that particular receiver or pedestrian. A processor keeps a table of authorized and unauthorized ID's within the safety zone of the machine. For authorized workers, no action is taken--for unauthorized workers warning signals are generated on the vehicle and sent to the endangered individual. This approach seems beneficial for eliminating some "nuisance" aspects of warning people who do not need to be warned--although making that discrimination would require processing as will be discussed below. Another example RF based system enables the dangerous instrumentality to transmit different signals (to be detected by affected pedestrians) for different threats, which differing signals can be discriminated by the pedestrian receiver, and which can result in different warning (audible, visual, tactile) for different threats.
Several of the examples referenced above disclose modifying the signal being generated by the dangerous or hazardous mobile instrumentality to convey more threat-specific information. An application of this example is shown in FIGS. 2A and 2B which disclose changing a shape of a transmitted warning signal from a forktruck based on the mode of operation or movement of the forktruck, for example, a gear selection of the forktruck (e.g., forward, reverse, neutral). An indication of the gear selection from a detector is provided to a transmitter carried by the forktruck itself, which creates and/or transmits a proximity signal that will be received by a receiver carried by a pedestrian, which receiver is capable of determining the signal strength of the received proximity signal. The detector, for example, may include a sensor to determine a property of vehicle movement such as, for example, whether the forktruck gear selector is in the forward position, neutral position and/or the rearward position and produce an output or signal representative of the vehicle movement property (e.g., the gear selector being in the forward position). The signal is modulated or generated based on that gear selection (and/or other indication of activity such as movement) of the forktruck so as to create an output or warning zone indicative of the mode of movement or the direction the forktruck is traveling. FIG. 1 shows an unmodulated warning zone 10 that has a circular cross section since the transmitter generates a field that radiates in all directions. As seen in the FIGS. 2A and 2B, a warning zone 10' is biased toward the front of the forktruck when it is moving forward, and biased to the rear, when the gear selector is in reverse. This may help avoid nuisance alarms--for example to a pedestrian who is positioned behind a forktruck that is moving forward. As used herein, the terms transmitter and receiver should be broadly construed to encompass at least the various forms of radiation (magnetic, RF, optical, infrared, etc.) described above and below.
Similarly and relatedly, the proximity signal generated by the transmitter on the forktruck is modulated by the speed and/or traveling direction of the forktruck to dynamically modify the shape of the proximity signal's "field" or warning zone. A faster-moving forktruck creates a larger zone, a forward-moving forktruck creates a zone shape biased to the front of the forktruck, and vice-versa for a backing forktruck. Such an example is depicted in FIGS. 3A and 3B, with FIG. 3A showing the warning zone 15 for a relatively slow-moving forktruck, and FIG. 3B showing the warning zone 16 for a relatively fast-moving forktruck. For a pedestrian outside either warning field of FIGS. 3A and 3B, but being approached by such forktrucks, the field or warning zone of FIG. 3B would result in receiving the signal earlier and with a relatively larger signal strength as compared to that of the signal from the slower-moving forktruck as in 3A.
The example of modulating the "warning field" for a forktruck based on operational parameters such as gear selection or relative speed is enhanced by using the position of the forktruck steering wheel as the source of such modulation. Forktrucks may be particularly dangerous by virtue of the fact that they are steered by the rear wheels as opposed to the front wheels as we are commonly used to from other vehicles (e.g., automobiles, etc). Accordingly, the movement or steering action of a forktruck can be potentially dangerous to an unsuspecting pedestrian. Modulating the "warning field" of a forktruck based on the steering wheel position or rotational direction can provide effective warning signaling to a pedestrian unfamiliar with this movement. A sensor monitors either the absolute position of the steering wheel, or the direction it is being rotated, and the shape or orientation of the warning field is modified based on that signal. In the example of FIG. 4A, a forktruck warning field 20 that is not modulated by a steering signal is shown. The curved arrow 30, and the straight arrow 40 indicate that when the forktruck is turning to the driver's right, the steered rear wheels will actually swing toward the depicted pedestrian (to the driver's left) who may not be familiar with this unusual motion. In the example of FIG. 4B, however, the warning field 20' is shown in both a "normal" orientation (extending in a forward direction from the forktruck), but also in a counter-clockwise rotated orientation due to the fact that the forktruck steering wheel has been turned to the right (meaning the rear wheels will be turning to the left). The modulated warning field may include only the second, rotated lobe or both. In addition, the warning zone may include a third lobe directed in a clockwise orientation relative to the forktruck to warn someone forward of the vehicle of the impending turn. Rather than the warning signal being divided into lobes (which is done here for purpose of illustration), a single field shape could be used to provide an indication of the soon-to-result turning movement of the forktruck. The modulation of the warning field for a turning forktruck may be performed in advance of the actual movement to give a prospective quality to the warning by using the rotational position and the rotational speed of the steering wheel as a modulation signal. An alternative is to provide the forktruck with a turn signal switch such that activation of the right turn switch by the forktruck operator (trained to activate the switch several seconds before initiating the turn) would serve as the trigger for modulating the warning field in the manner of FIG. 4B. Thus, systems or sensing apparatus to modulate a proximity-based signal with threat-relevant information (e.g. the status of the forktruck gear selector, or its speed or direction) to allow more effective warning based on that threat-relevant information are disclosed herein.
Another example of a proximity based detection system for hazards uses visual light to create a warning field that can be detected by sensors, but that is also visible to the eye. As depicted in FIGS. 6A and 6B, a forktruck FT is fitted with one or more light sources 40. Illustratively, four light sources (front, back, left and right) are provided, with the capability of projecting both red and green light. For normal operation of the forktruck (i.e. when it is driving in a generally forward direction through the facility with no detected hazards), the forward light source 40 is illuminated green to project a cone-shaped signal 50 on the floor in front of the forktruck. In this case, the front light is illuminated as the forktruck is moving in a forward direction. Alternatively, a different shape is used for the forward signal including a forward signal the shape of which is modulated by the speed of the forktruck (as in previous examples, the shape would extend further forward or be larger in the forward direction for a faster forktruck speed in that direction). One way to achieve this modulation is to provide the light sources 40 with adjustable apertures, lenses and/or adjustable positioning so that the shape and direction of the light sources can be modulated based on inputs from other sources such as, for example, a speed and direction indication received from the forktruck, although other sources could be used. In another alternative, shown in FIG. 6B all of the light sources are illuminated green in this condition of the forktruck moving generally forward through the facility, in effect creating a "zone of safety" around the forktruck. The green illumination (either only in the forward direction, or surrounding the forktruck, or taking other shapes) serves as a visual indication to the forktruck driver that the path he is pursuing is "safe" (no pedestrian interactions have been detected), and also as a visual indication to surrounding pedestrians that the path of the forktruck is "safe" insofar as close-proximity pedestrians have not been detected. The projection and ability to perceive these "light signal" may be enhanced by painting the floor of the facility with a reflective paint, or by adding reflective grit to the concrete floor when poured.
The examples described above using visible light as the basis of a proximity-based hazard sensing system can be applied or implemented with other systems. For example, a particularly common industrial accident is a forktruck running over a person's foot, which most often happens when a stationary forktruck near a pedestrian begins moving. To address this specific situation, a forktruck could be outfitted with light sources 40 like those shown in FIG. 6A. In this example, however, the light sources could be a single color, or even a non-visible light (e.g. an infrared light), and would always be projected in a warning field surrounding the forktruck, such as a circular warning field. Alternatively, since this accident is most common with a stationary forktruck, the warning field could only be projected when the forktruck is stationary (either by detecting a lack of motion, or by determining that the gear selector is in the neutral position). In either event, the workboots of pedestrians are equipped with light sensors designed to detect the wavelength of light projected by the light sources above a given illumination level indicative of a predetermined unsafe (or potentially so) proximity to the forktruck. Whenever a pedestrian is close enough to the forktruck for the warning field to be sensed by the light sensors, a warning signal may be provided to the pedestrian, the forktruck or both. This may be particularly effective if the warning field is only generated when the forktruck is stationary, as receipt of the warning signal by the pedestrian indicates that he is close to the forktruck, and preferably raise his awareness of the situation to be cautious about the forktruck beginning to move. As a further enhancement, a communication channel between the pedestrian and the forktruck would receive an indication of the light sensor detecting the hazardous condition--resulting in corrective action. For example, the forktruck could be prevented from moving if such detection occurs, or a warning signal could be provided to the forktruck operator of a pedestrian in dangerously close proximity. The operator may be able to visually identify the affected pedestrian and override the warning to begin moving the forktruck, or the system could be latched in a way that movement of the forktruck is not possible until the pedestrian moves away from the warning field of the forktruck (e.g., to a far enough distance away from the forktruck) so as to not be endangered by the forktruck then moving.
The use of color can also be applied in a different way to achieve some of the safety goals of this disclosure. Rather than having a forktruck carry light sources, however, this example divides a given facility into different zones which have differing safety levels. One zone may be a generally open area in the middle of a warehouse space where typically only forktrucks are present, and few pedestrians enter. Another zone may be the loading dock area of a warehouse, where pedestrians and forktrucks typically both reside. A third zone may be a corridor where forktrucks are present that is just beyond doors into meeting rooms, offices, or other people-only spaces (these can be particularly dangerous corridors). The floor of the different zones are each painted a particular color--chosen to be indicative of the danger level vis-a-vis a particular hazard--in this example pedestrian-forktruck collisions. Since the first, open zone described above is generally a low-danger area relative to such collisions, the floor of that area may be painted a first color, illustratively blue. The loading dock area or zone is of a relatively higher danger level, and might thus be painted yellow. Finally, the zone or corridor outside the meeting room area is potentially highly dangerous and might thus be painted red. It should be noted for the purposes of this discussion that the term "paint" or "painted" should be broadly construed to include not only actual paint, but also, for example adding a coloring agent, such as a colored grit to concrete as it is poured or any other way to achieve the desired effect of coloring the floor a particular color. The painting or coloring of the floor in the various areas thus serves as a visual indication to pedestrians and forktruck operators alike about the potential threat level in that area. Alternatively, a zone-based indication using color could be provided by modulating the colors of overhead lights in the various zones, to similar effect.
In addition to providing a visual indication, the floor coloring can also be used to modify the operation of the forktruck to take the potential threat level into account. In that regard, the forktruck can be fitted with a color detector that can detect whether the forktruck is in a "low-danger" blue area, a "raised danger" yellow area, or a "highly dangerous" red area. Based on the type of zone in which the forktruck then resides, operational parameters of the forktruck can be modified. For example, in a blue zone, no modifications might be made. In a yellow zone, however, a speed limitation may be imposed on the forktruck. In a red zone, the forktruck might become inoperable upon entering the zone until a particular safety protocol is carried out and verified.
The differing zones could also be used to modify the operational parameters of other systems besides just the forktruck. Different sensing mechanisms for detecting hazards could be used in different zones. For example, a robust, sophisticated hazard detection system might require large amounts of electrical or computing power to be effective. If such a system is carried with a pedestrian, power consumption is an issue, as a power source such as batteries, and a computing source such as a processor must also be carried. Accordingly, to limit power consumption, it is desirable to only use this system in high-danger areas. If the pedestrian carried a color detector, some example systems are programmed to only activate and power the hazard detection system when the pedestrian is in a high danger zone (e.g., the red zone), and to use different hazard detection system(s) in less dangerous zones (e.g., the blue zone). Some examples apply the same approach to the forktrucks or to providing warnings in which different types of warning are presented to potentially endangered actors depending on which level zone the actor is in. It is also the case that "zones" could be established in other ways besides the coloring of the floor in given zones. Generally, zones may be provided in a facility according to the potential danger related to specific events (such as forktruck-pedestrian collisions), and that operational protocols, hazard detection schema, threat communication schema, etc., can be modified based on the zone of activity or interaction.
FIG. 6C is a flow diagram representative of example machine readable instructions 6000 that may be executed to implement a system to detect and/or warn of hazards in different ways for different areas of a building. At block 6002, the system determines threat levels for a hazard in respective ones of different areas of a building. For example, the different areas may be "highly dangerous" areas, "relatively low dangerous" areas, etc. This determination can be made based on historical data (e.g., number of accidents in a given area), empirical data (e.g., types of locations that are expected to have heightened risk of collision), or on manual input (e.g., rankings). Irrespective of how the threat levels are assigned to areas, the system assigns two or more different hazard detection systems for use in different areas of the building (block 6004). For example, a first detection system may have a first ability to detect a particular hazard and a second detection system may have a second ability different from the first ability to detect the particular hazard (block 6004). For example, the first detection system may be a robust, sophisticated hazard detection system to be used in building areas identified at block 6002 as relatively high danger areas and the second detection system may be a less sophisticated (and likely less expensive in costs and/or computing resources) hazard detection system that may be used in relatively low danger areas as identified at block 6002. Once the systems are deployed in accordance with the assignment made at block 6004, the system employs the first detection system to monitor for the particular hazard in a first area assigned a first threat level (block 6006), and the system employs the second detection system to monitor for the particular hazard in a second area assigned a second threat level (6008). In some examples, the system modifies the operational parameters (e.g., limit the speed) of a forktruck based on the area in which the forktruck is located (block 6010). For example, when entering the first area (e.g., an area considered to be a relatively high threat area), the robust first detection system may have the ability to automatically enforce a speed limit via an electronic control signal on the forktruck or may send a suitable warning to the forktruck that it is in a high danger zone.
Other ways of determining "zones" of different threat levels can also be employed. For example, one zone may be considered more dangerous than another based on population or traffic density--a higher density arguably representing a greater threat. Creating zones based on population density can be done statistically (such as by monitoring areas over time and assigning densities to various areas based on the results), or dynamically such that the area of a more dangerous "high density" zone can change over time to reflect changed circumstances in a given parameter like population densiry. There also may be a temporal component to a given zone being considered more or less dangerous. For example, an operation that only loads trailers on third shifts, the loading dock may only be designated as a "high risk" zone during this time, and be designated "low risk" at other times.
At least some of the sensing systems described above rely primarily on signal strength to determine proximity, and thus the existence of a danger. In some cases, the proximity sensing is enhanced by signal processing to indicate direction as well as distance to the hazard. Some processing of these signals to discriminate among the level and immediacy of threat has also been described. Even so, a system relying on relative position data has potential limitations on resolution, accuracy, timeliness, etc.--although with the advantage of a relatively inexpensive implementation. A system that would allow more accurate and more absolute determination of position, direction, velocity, etc. might provide a higher fidelity of warning, although likely at an increased cost in terms of both component cost and system complexity.
Other example systems include absolute location technology for enhancing the determination of proximity of a dangerous instrumentality (e.g. forktruck) and a threatened object or person (e.g. a pedestrian). In such systems, both entities typically have the ability to determine their absolute location via, for example, Global Positioning System (GPS) technology and/or one or more other technologies. The acronym "AL" will be used herein as a general term for such absolute location systems. Knowing the absolute location of both entities allows their proximity to be determined, and appropriate action taken (e.g. hazard warning) if that proximity is indicative of a hazardous situation. Accordingly, the first example system described herein are based on proximity (in terms of determining threats) enhanced by AL technology. For example, in one such system, both an earth moving machine and objects in its vicinity (vehicles, pedestrians) have AL capability. A communication channel exists between the machine and the objects through which the objects transmit their self-determined location to the machine. A processor on the machine translates the location information into a graphical depiction of the machine and the objects in proximity. The objects can also transmit an identifier, which allows not only their position, but an indication of the type of object they are to be shown on the graphical interface. In this case, the operator, armed with this information, is empowered to take appropriate action based on the represented proximities. This system may also be configured to determine the accuracy of the position location of the object, and modifying the display based on that information--lower accuracy of position resulting in the object being depicted as larger and vice-versa. Additionally or alternatively, the system can modify the display based on other information about the object. For example, if a unique identifier is provided by the object, the machine (in this example) could maintain look-up information (e.g., a look-up table) about that object such as, for example, their authorization to be in certain areas, or in certain proximity to a forktruck, the level of safety training received, whether that person is a supervisor or employee with heightened awareness of hazards, whether that person has been in a high number of accidents, etc. The display could then be modified based on this information, for example, someone with authorization is depicted as small (since their authorization suggests adequate training on safety issues and thus a reduced risk relative to other less-trained pedestrians), while the novice or person prone to accidents would receive a larger icon (indicative of requiring a larger personal safety zone given his status). Furthermore, the system could be enhanced by also providing threat-specific information about the proximity or potential for danger back to the affected objects, as will be discussed in more detail below in the section regarding communication.
Another example system using AL having dangerous instrumentality (typically an emergency vehicle, which is not necessarily dangerous on its own, but is when en route to an emergency and requires a cleared path) can itself determine the nature of the safety zone it needs to create around it (for example, based on its location, speed, direction, course to the emergency, etc.) and broadcasting a signal with such information. Its ability to formulate and broadcast such a message is facilitated by the presence of an AL system. Accordingly, the broadcast signal will typically include AL-type coordinates delineating the safety zone surrounding the emergency vehicle and extending along its projected path, on either a temporally static or dynamic basis. The receiving entities also possess AL capability. They thus receive and decode the broadcast signal, which includes information about the boundaries of the danger zone, and determine based on their then-current AL position whether or not they are in the danger zone. Appropriate action can then be taken based on that determination (e.g. a warning signal generated). Given the existence of AL technology in these systems, significant levels of sophistication are possible. For example, one system showed the receiving entity as generating specific danger-averting directions to affected vehicles in the path of an emergency vehicle ("forktruck approaching from the north behind you, pull to the left and stop" "forktruck approaching you from ahead, proceed with vigilance" etc.). As will be described below, such threat-specific warning/direction is desirable, giving a "personal" aspect of the personal safety zone. Since the broadcast warning signal can be created (or modulated) based on threat-specific information, and since the receivers can be programmed to know their own status and position (based on AL), the sending instrumentality can effectively create multiple zones simultaneously. In the example of pedestrian/forktruck interaction, the forktruck sends information based on its speed, direction, and course identifying a dynamic danger zone. Additionally, the forktruck could also send that information with one threat level for certain kinds of personnel (e.g. managers, supervisors, highly-trained individuals, and/or other employees who are authorized to be in an otherwise dangerous locality based on the current task they are performing), and another, higher threat level for other personnel. Moreover, the size and shape of the two zones just referred to could be chosen to be different--presumably a larger safety zone for less-trained personnel. As mentioned, several of these example systems included the ability to take the route to be traveled into account in creating the shape and size of the warning zone. Such functionality is very desirable in the context of forktruck/pedestrian safety as a significant risk in this application is created by narrow, blind corridors and corners, for instance between racking. If the processing capability on the forktruck can determine or account for the racking layout relative to its own current or projected course, that layout (and attendant increased risks) could be figured into the logic of formulating the nature of the broadcast danger zone. Further, the broadcast signal could, in appropriate circumstances, include some kind of indication that there is not only a hazard, but that it involves a blind corner or alley allowing a heightened warning or corrective mechanism to be sent or conveyed to the recipient once the signal is decoded. Such heightened level warnings are significant in this application, since the threatened person may not be able to perceive the impending threat even when warned, but a "blind alley" warning could alleviate the problem. Better still is the ability to give more accurate information about the direction and imminence of the threat. Providing this, however, could require enhanced processing capability being carried with the recipient of the signal, which could be undesirable given size and power limitations. Compensating for those requirements while still giving the desired functionality is desirable.
At least some of the preceding examples included sending instrumentality that determined the nature of the threat and the appropriate zone. But, again, with adequate processing power at the location of the recipient, this need not be the case. In another example, two or more entities of interest (e.g., two vehicles) may be implemented with AL capability. The first entity of interest sends location, speed, heading, etc., information. This information is received by the second entity of interest, which compares this information with its own (speed, heading, etc.) to determine if there is a risk of collision or other hazard. In some examples, the first entity of interest corresponds to a forktruck and the second entity of interest to a pedestrian, but in the interest of keeping significant computing needs from the pedestrian, this could be reversed. If, for example, each pedestrian had an AL unit, along with a relatively simple accelerometer or other speed/heading-determining device, the AL unit could periodically broadcast this information. Forktrucks would have an adequate power and size platform for the computing power necessary to receive such periodic signals, and determine based on the position and movement of the pedestrians whether hazards existed. The forktruck operator could be notified to empower him to take preventative/corrective action. Further, given the existence of a communication channel, the forktruck could communicate back threat-specified or otherwise enhanced personalized warning to the affected pedestrians. As before, if mapping of the facility were included in the programming given to the forktruck, it could take especially hazardous situations into account in performing this function, such as pedestrians down "blind" alleys or corners--and appreciate the enhanced danger and take appropriate action or send appropriate warnings (or both) based thereon.
Such AL based technology could be used to enhance its functionality and provide some of the features and benefits of a Personal Safety Zone system. One example is to provide pedestrians with the machine vision capability forming the AL aspects of this approach. In essence, this would make both forktrucks and pedestrians visible and trackable in and by the central processor. Software routines could then be written to process this data and look for potentially dangerous situations, such as collisions. As noted above, however, it is perceived that the cost and complexity of such systems that is portable enough to be carried all the time by a pedestrian are probably too high. Other technologies that would potentially allow AL of all objects (forktrucks and pedestrians) do exist, and will be discussed below. Instead, for example, an AL system like that disclosed for forktrucks alone may be used, because the forktrucks typically have the necessary size and access to power to allow practical AL to be performed. That AL information will be provided to the central processor which will be capable of tracking the movement of forktrucks through the facility with the demonstrated mapping of facility structure (walls, racking, etc.). Where this example differs from existing systems is in how the AL information in the central processor is used to determine dangerous situations and provide more effective, and preferably, more personalized warnings of those dangers. For example, FIG. 7 illustrates a forktruck F moving between two rows of racking R toward a double-blind (blind in both lateral directions) intersection 70 with pathway P. Rather than use the central processor to illuminate a beacon at the intersection and provide a generalized warning that might be easily missed or ignored, an alternative is to have the central processor formulate a threat- and/or location-specific warning based on the specific hazard to be conveyed to affected pedestrians (e.g. those within the potential danger area). Potentially affected pedestrians would have the ability to receive the threat-specific warnings. For example, if the aisle the forktruck is moving down is designated as aisle 6, given the AL and tracking ability of the central processor, it is capable of formulating a warning such as "Forktruck approaching intersection from aisle 6, heading north--use caution" to be conveyed to pedestrians approaching that blind intersection from either direction along pathway P. That message would then be conveyed to some means for communicating that message to the potentially affected pedestrians.
It may be desirable for this message to only be conveyed to pedestrians that could actually be harmed by the forktruck approaching that intersection. There are different methods or ways to achieve that end. One category of such approaches would be "passive" communication systems, in which the threat-specific warning is conveyed irrespective of whether endangered pedestrians have been detected in some manner. For example, the warning could be broadcast by conventional RF transmitters 72a, b illustratively positioned on the ends of the racking R adjacent intersection 70, and any RF receivers within a given range could detect the signal. Illustratively, the field shape or range of that transmission could be modulated based on the nature of the threat to selectively warn pedestrians in a certain proximity or direction from the threat. The central processor could use AL position and heading data to determine the size of the area adjacent, for example, aisle 6 intersection within which pedestrians could be harmed if the forktruck continues its then-current trajectory (referred to in this context as the "danger zone"). The size of that area would presumably get smaller as the forktruck F got closer to the intersection 70. In addition to the warning message itself, the central processor could also provide the RF transmitter with the information about the size and shape of the danger zone. The transmitted warning signal would not only convey the message, but would only be broadcast to be received with adequate signal strength by only those receivers in the danger zone. Such an arrangement may place an RF transmitter at or adjacent the "danger zone" in question which could be addressed by the central processor.
In an "active" communication system, warnings (general or endangered-pedestrian specific) are generated only when there is the potential for danger based not only on forktruck approach or presence, but also the sensed presence of a threatened individual. Some means for detecting the presence of such an individual will be required in such a system. Some example systems employ motion or presence sensors such as, for example, the I-Zone sensor used by Rite-Hite Doors, Inc. of Milwaukee, Wis. to detect the presence of moving objects adjacent a closing high-speed door. A semi-cylindrical lens with alternating masked and unmasked sections divides the field of view of a passive IR sensor into spaced fan-shaped detection areas. According to the logic, an IR signal has to be detected by consecutive detection areas within a given timeframe to trigger a detection event of a moving object. Other forms of presence/motion detection can be employed. Such a sensor is installed at the potentially hazardous intersection 70 of FIG. 7 (although this is only an illustrative example). An approaching forktruck (as determined by the AL central processor) makes the sensor "hot". In some examples, the sensor may continuously sense an area and send output signals, and the output signals may be ignored until the area is hot. In other examples, the sensor is only powered when the area is "hot" or a dangerous condition is sensed. Either way, the potentially dangerous approach of a forktruck to the monitored area makes it "hot" for the detection of people. Such a detection event can trigger a generalized warning, or a threatened-pedestrian specific warning assuming that an adequate communication channel exists to allow for such. Safety could be enhanced by also communicating the detection of the person in the hot zone back to the forktruck driver or even imposing speed governance on the vehicle in such a situation.
Relatedly, other technology could be used to determine if there are pedestrians in the danger zone (e.g. RFID radar, triangulation with RFID, actual or localized GPS, or ultra-wideband UWB detection). As above, such detection systems could continuously monitor a dangerous intersection (e.g., the intersection 70 of FIG. 7), and the output signal could be ignored until a centralized AL system detects an approaching forktruck F. Alternatively, the centralized AL system could activate or make "hot" such detection systems only when the forktruck F approaches intersection 70 and a potentially dangerous situation is detected. Once endangered pedestrians are detected, threat-specific warnings are sent to them. If a system is used (e.g., RFID) that also allows identification of the pedestrian, a truly personal warning (e.g., Tom, a forktruck is approaching) could be conveyed.
In other examples, instead of use of an AL system to identify that the forktruck F is approaching the intersection 70, other systems could be used such as a photoeye/reflector described above. Detection of the approach of a forktruck could activate or make "hot" a system for detecting people in the danger area. Thus, a comprehensive system for comprehensively monitoring (e.g., every square inch) of a facility may not be required. Rather, it may be possible to identify high-risk area, like intersection 70, and invest in a relatively more sophisticated, robust detection/sensing systems for that location to work in conjunction with lower level sensing to achieve enhanced safety. Indeed, an industrial facility may be implemented with a patchwork of the example sensing/detecting regimes described herein, along with associated communication channels and techniques. In this manner, choices can be made about the appropriate sensing and communication in given areas given the perceived risks of danger in the various areas. Thus, a system can be implemented that is tailored for different parts of a facility that have different levels of risk (e.g., blind intersections and doorways opening into forktruck aisle ways being particularly dangerous, while open floor space being generally less so). Employing different sensing/communication regimes (some more of which will be described below), an optimized system can be implemented where the appropriate regime is selected and implemented based on the perceived risk of danger in different areas of the facility.
Different examples of systems based on AL of forktrucks have been described herein, for example using the previously-mentioned machine vision system. The first example was "passive" in that general warnings were given in potentially dangerous areas being approached by a vehicle without regard for whether or not an individual was there. The next level was an "active" system for determining the presence of an individual in a potentially dangerous area, and providing warning only in that situation. Sensing can employ presence/motion sensing devices or AL devices that may also facilitate the formulation and delivery of effective, personal warnings. In other examples, described below, all objects are located and/or tracked.
As with the proximity-based and more limited absolute location systems described above, different types of instruments or technologies are available for location and tracking the entities of interest (e.g., forktrucks and pedestrians). Such example systems have already been described relative to forktrucks, and the machine vision technology used in such systems can be configured or adapted to pedestrians as well. In that context, however, it might be optimal to reverse the location of the location markers (bar codes, etc.) and the cameras viewing them so that the bar codes move with the tracked entities, and the cameras are fixedly mounted in the ceiling. This prevents the need for each pedestrian to have to carry the weight and associated electronics and power source of both a camera and networking components. However, line of sight issues with bar codes on people could limit this approach. Other camera or optically-based systems for locating and tracking people, however, could be adapted for this application. For example, camera and image-processing technologies exist for the purpose of locating and tracking shoppers in retail settings--to determine what kinds of displays they might be attracted to, and to study shopping and dwell time patterns. Generally these systems employ image processing to raw video images to look for image patterns associated with people. An image pattern for a given individual is then tracked as it moves throughout the space. Algorithms can then be applied to the image data to extract useful information about movement patterns and dwell times at particular locations. Such systems can then correlate locations to specific product displays to provide useful marketing feedback and information. Other uses of this technology include security and patient-monitoring applications. Such systems can have a very high level of sophistication, but this can come at the expense of relatively large processing power and time requirements, as well as relatively high costs. A benefit, however, is that the entities of interest do not need to be equipped with any special equipment to allow them to be located and tracked.
Another example system employs technology that is similar, but that is advertised as not being subject to the limited range applications of RFID is ultra-wideband (UWB) technology. Here, tracked entities of interest also carry tags like in the RFID setting. An array of UWB interrogators are distributed throughout the facility and use a variety of techniques (e.g. triangulation, Doppler processing, etc.) to locate and track entities based on the response of the tags to interrogation signals. Examples of use of UWB technology includes social networking settings, in which the central processor not only locates and tracks all of the individuals, but also performs processing on stored characteristics for each individual so as to identify when two individuals in close proximity share a common interest. A communication channel from the central processor informs one or both individuals of the match in interests to allow them the opportunity to have a direct interaction. Some examples provide the information to an individual in a "heads-up" display embedded in their glasses.
As mentioned above, the great flexibility and optimization of these various sensing and/or locating and tracking technologies can be beneficially implemented in that the optimal technology can be selected for a given application. Different parts of a facility may represent a lower risk of an accident, and can thus be monitored by a lower level (and likely lower-priced) technology option. Similarly, a given technology may be better suited to the sensing or locating/tracking of a given entity (e.g. a forktruck or a person). If that is the case, separate technologies could be used for monitoring the location of forktrucks versus people. It may also be possible to use level of technology for "gross" location (e.g. RFID) and to then switch to another technology (e.g. based on line of sight) for "finer" location (e.g. when the entities are less than ten feet apart). Given these realities, and the desirability of being able to provide the most effective and reliable safety system for the best price, an aspect of this disclosure is the identification of appropriate sensing/locating/tracking technologies, combined with an application knowledge of the types and nature of hazards at different parts of a facility to create an integrated system of perhaps one, but likely several such technologies that provides a cost-effective way to achieve the desired safety goals.
The example systems described herein may be employed with sensing/locating/tracking to provide enhanced industrial safety systems In addition, the data generated by the example systems regarding the entities of interest may be analyzed to determine the possibility of hazards and to allow the formulation of appropriate responsive action (e.g., in the form of warnings). For the purposes of this description, this analysis of the data regarding the entities of interest will be referred to as "hazard discrimination" and performed by what we term a "hazard discriminator".
Some of the example systems described above employ a low level or simple form of hazard discrimination. In the example system employing proximity-based sensing systems, hazard discrimination came in the form of detection of signal strength above a certain threshold. In the case of the forktrucks sending out RF signals being detected by receivers carried by individuals, the detection of that above-threshold signal strength served as hazard discrimination in that the threshold was selected such that detection was indicative of a potentially dangerous proximity of the transmitting forktruck. In that case, hazard discrimination was distributed and performed locally by the potentially-endangered entity--in this case the pedestrian. This type of distributed hazard discrimination could also place the hazard discrimination on the forktruck. In the example described above in connection with FIG. 5, a forktruck included a directional antenna array, which gave input to a GUI which depicted the locations of pedestrians relative to the forktruck (FIG. 5). With just the GUI, the judgment of the forktruck operator would represent the hazard discriminator, but the processor needed to generate the display could also perform hazard discrimination. In that case, for example, the processor detects when a sensed pedestrian is within proximity of the forktruck considered as dangerous. Note that hazard discrimination in this context is not limited to forktruck/pedestrian interactions, but could apply to forktruck to forktruck interactions, or forktruck to fixed object. The discriminator could be programmed to apply different thresholds for different threats. For example, the distance threshold for identifying the proximity of another forktruck as being dangerous is smaller than the threshold for a pedestrian, since the approaching forktruck has the ability to move faster than a pedestrian. Preferably, the hazard discriminator would have the flexibility to be programmed with different operations for different situations in this manner. Another example of the forktruck performing hazard discrimination would be a case where pedestrians are wearing RFID tags and the forktruck is equipped with a reader and an ability to determine, for example, the time delay between sending of an interrogation signal and receipt of response to give an indication of the location of the pedestrian. A time delay below a threshold is considered by the hazard discriminator to be indicative of a pedestrian in dangerous proximity to the forktruck. Other hazard discrimination operations could be applied.
Hazard discrimination based on proximity is not, however, limited to a distributed basis. Proximity could be the relevant metric for a centralized hazard discriminator using as input detailed location/tracking data about all entities of interest. Again, depending on the application, that data may be provided by different sensing/locating/tracking technologies for different entities of interest. Even so, the centralized discriminator could be programmed to use a proximity hazard discriminator or operation to discriminate hazards. For example, the centralized discriminator may access a facility layout database and can be configured to calculate the distance between different entities of interest to determine when proximity between entities of interest is indicative of a potential hazard. Again, interactions between different entities of interest (forktruck/pedestrian v. forktruck/forktruck) may require different thresholds or operations for determining the existence of a potentially dangerous situation. Moreover, whether proximity-based hazard discrimination is performed on a distributed or centralized basis, it may be desirable to establish multiple thresholds for specific interactions of entities. For example, in the case of an interaction between a forktruck and a pedestrian, the hazard discriminator may be programmed to consider a first proximity as potentially dangerous and requiring continued attention by the discriminator--but not yet rising to the level where any corrective action (e.g. warning signaling) is indicated. If subsequent analysis (within some meaningful timeframe) of the proximity of the entities indicates that they are even closer, and below a second predetermined threshold, the discriminator may be programmed to consider that proximity as a relatively higher potential danger, and thus initiate a first level of warning signal (the term "initiate" is used broadly here, as the discriminator itself may not generate the actual warning signal, but could provide an output or signal level when that level of threat is detected, which signal could be used by another component or sub-system to actually formulate and deliver the warning). Finally, if the entities continue to draw closer in a temporally meaningful period, as indicated by subsequent analysis of proximity data, the discriminator could be programmed to determine this proximity as falling below a third threshold, and be indicative of an imminent collision. Such a determination would then initiate or trigger an even higher level of corrective action such as providing a more forceful or discernable warning, or applying the brakes or disabling the engine of the forktruck to prevent its further movement. The benefits of such a phased approach to hazard discrimination and warning include the reduction of nuisance warnings, pedestrians and forktruck operators get notification-level warning when the threat is low, and immediate-attention-required level warning when danger is really imminent--in the hopes that they will pay attention and respond to the latter, while having at least their awareness raised by the former. Indeed, in the scenario just described, some level of potentially dangerous proximity as determined by the hazard discriminator does not even result in any warnings, so long as the threat of potential danger does not increase when the data is analyzed at a later time.
In addition to providing this type of enhancement to proximity-based detection, a central locating/tracking system can provide other benefits that a distributed proximity-based system cannot (e.g. one based on signal strength detection alone). For example, the processing capability needed for tracking over time, allows the hazard discriminator in such a system to include an aspect of predictive analysis within its operation. An example of this predictive ability is illustrated in FIG. 9A. There, a first data point of a forktruck F and a pedestrian P are represented by open circles. The second data points (taken later at some predetermined interval) are represented by closed circles. Note that the separation between the data points for the forktruck is further spaced than that for the pedestrian indicating the forktruck moving at a faster speed. In this example, the hazard discriminator is capable of determining both the speed and direction of both entities and calculating a trajectory vector V for each entity. The hazard discriminator compares the two trajectory vectors V (sub-designated "p" for pedestrian and "f" for forktruck to ascertain whether continued movement on that vector would result in a collision, and, if so, initiate corrective action. Realistically, however, movement of such entities rarely continues on the same vector for an extended time. Accordingly, an improvement to pure vector analysis will be referred to herein as trajectory vector expansion which enhances the predictive value of vectorial analysis. Under this technique, the trajectory vector of each entity is expanded according to a predetermined expansion factor. The expansion factor can be calculated based on a variety of factors, such as speed range of the entity (large for forktrucks, small for pedestrians), acceleration capability of the entity (again large for forktrucks, small for pedestrians), the agility of the entity (smaller for forktruck, larger for pedestrians if defined as the ability to change direction with a relatively smaller linear displacement), and possibly other factors. According to the technique, whenever a trajectory vector V is calculated for a given entity, the expansion factor is then mathematically applied to result in an expanded trajectory vector E, as depicted in FIG. 9B, and sub-designated "vp" for vector-pedestrian and "vf" for vector-forktruck. Comparison of the two figures demonstrates the potential value of this type of analysis. According to the unrefined operation of FIG. 9A, the vectors do not intersect, and a potentially dangerous situation would thus not be indicated. In the example of FIG. 9B, however, the expansion of the trajectory vectors results in overlap 130, which could be interpreted by the discriminator as indicative of a potentially dangerous situation. In the current example, the trajectory vectors V are expanded. Rather than applying an expansion factor to the vectors, for example, the unexpanded vectors could be analyzed. Rather than requiring overlap of the vectors, a dangerous condition could be indicated by a proximity of the vectors within a given range (e.g., the condition indicative of a hazard is expanded, rather than the trajectory vectors themselves). In this example, the proximity indicative of a dangerous condition is predetermined based on a variety of factors such as entity speed range, acceleration, agility, etc.
An alternative example for using a centralized location/tracking regime for entities of interest uses a hazard discrimination technique involving an analysis similar to Venn diagrams to determine potentially dangerous situations. In this example, the central processor draws figures around entities of interest indicative of a safety zone around the entity. While the simplest safety zone figure for such use is a circle, other safety zone figures that take factors into account about the entity are also possible. For example, the determined direction of movement of an entity of interest could alter the shape of the safety zone figure. As shown in FIG. 10A, the pedestrian entity P is moving to the right in the figure. Accordingly, the safety zone figure for that entity of interest is calculated as being biased in that direction, for example, as an oblong shape with greater area in front of rather than behind pedestrian P. The size and shape of the safety zone figure is modified based on the recent movement history of the entity. In other examples, the size and/or shape are modified based on other information such as the level of training or experience of the given entity of interest (such information being stored, for example in a lookup table accessible to the processor). In that case, an individual with higher training might have a relatively smaller safety zone figure since his increased safety awareness from the training might reduce the area in which other entities might represent a threat to him. Similar modification of the size and shape of the safety zone figure could also be carried out for forktruck or other vehicular entities, with, for example, the average speed of the vehicle over time. For a "fast" forktruck driver, the safety zone figure is relatively larger, since his higher speed represents potential danger in a greater area. Hazard discrimination is carried out by the processor by calculating and updating safety zone figures for all entities of interest. A hazard discriminator then dynamically seeks overlaps of the safety zone figures (such as the safe zone figure 140 in FIG. 10A) to determine potential hazards. This is analogous to Venn diagrams where overlapping regions of two-dimensional safety zone figures representative of set spaces is indicative of common set members for the spaces represented by the safety zone figures. The hazard discriminator could look simply for any overlap between the safety zone figures of all entities, and initiate corrective action when overlap is found. However, in other examples, as overlap is first found, the system (e.g., via a processor) monitors the development of the size and shape of the overlap of the safety zone figures for these two entities. Presumably, as the entities draw closer, the overlap would increase. The processor could be programmed to initiate higher levels of warning based on a determination of an increase in the size, or change in the shape of the overlap indicative of greater danger. A similar technique could be used for taking fixed obstacles (walls, racking, etc.) into account. In that scenario, the processor is programmed with the coordinates of such obstacles, since the presence of an obstacle between two entities may reflect a situation where they cannot collide on their current trajectories based on the presence of the obstacle. In such examples, the processor is programmed to ignore an overlap in the safety zone figures of two entities of interest. This is done, for example, by ignoring an overlap for an interposed obstacle, and/or by dynamically modifying the shape of the safety zone figures for the entities to take into account their proximity to a fixed obstacle, insomuch as the presence of that obstacle impacts the possible path trajectories for that entity.
The safety zone figure technique could also combine both actual overlap of figures with their relative proximity. For example, a close proximity of figures without overlap could trigger the processor to monitor those entities for a reduction of that proximity, up to and including their actual overlap. Potentially, the processor could be programmed to initiate corrective action (warning, signaling, etc.) based only on such proximity of figures instead of waiting for the threat to rise to the point where the figures actually overlap. The processor similarly could be programmed with determinative operation based on past movement patterns of the entities to predict likely movement paths and modify the safety zone figures accordingly. Potentially, such analysis could also lead to the processor initiating corrective action before a potentially hazardous situation actually occurs--perhaps resulting in low-level warning being initiated to raise the awareness of the entities to potential danger based on their current position, and the likely path of such entities based on history.
As mentioned above, the example processes of FIGS. 6C, 8, 9C, 10B and 10C may be implemented using coded instructions (e.g., computer readable instructions) stored on a tangible computer readable medium such as a hard disk drive, a flash memory, a read-only memory (ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, a random-access memory (RAM) and/or any other storage media in which information is stored for any duration (e.g., for extended time periods, permanently, brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term tangible computer readable medium is expressly defined to include any type of computer readable storage and to exclude propagating signals. Additionally or alternatively, the example processes of FIGS. 6C, 8, 9C, 10B and/or 10C may be implemented using coded instructions (e.g., computer readable instructions) stored on a non-transitory computer readable medium such as a hard disk drive, a flash memory, a read-only memory, a compact disk, a digital versatile disk, a cache, a random-access memory and/or any other storage media in which information is stored for any duration (e.g., for extended time periods, permanently, brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable medium and to exclude propagating signals. For any of the hazard discrimination techniques described herein, determination of a potentially hazardous situation may not result in initiation of corrective action in the form of direct warnings. Rather, the central processor could be programmed to take other corrective action. In the example depicted in FIG. 11, a pedestrian P is about to enter a potentially dangerous high-traffic area as he enters the loading dock area LD. Assuming that the processor has some means of directly or indirectly controlling an actuable barrier B, such as a safety gate or door, the processor can determine that entry of the pedestrian P into the loading dock LD area is unsafe, and actuate the barrier in advance of the pedestrian P entering the area. Actuation of the barrier would not only physically prevent entry, but would also serve as a form of warning to the pedestrian. If coupled, for example, with a signaling apparatus (e.g., lights) closing of the barrier could also sensitize the forktruck drivers to the presence of a pedestrian. In an attempt to ensure respect for the hazardous situation, the system could prevent the barrier from opening until some form of acknowledgement of the danger by the pedestrian. For example, he could be required to enter a security code, or to await receipt of an audible warning at the site before the gate opens. One could also envision a situation where the forktruck operators are empowered with opening the barrier--but only after some form of acknowledgment of the danger, and then only opening the barrier when the condition is perceived by him to be safe, such as by a visual inspection of the area, or by direct verbal or other contact with the affected pedestrian.
Sound-based or aural communications of threats to an endangered pedestrian (or other individual) are made more effective by allowing the endangered pedestrian himself to select the warnings or communication he will receive. One example of this allows an individual to select the actual warnings he would receive by selecting the content for different tracks on an MP3 player that he will carry with him and that will be the source of his personalized warnings. One way of allowing for such a personalized selection of warnings is for a pedestrian to actually record warnings of his choosing and in his own voice to provide warnings for given situations. A list is provided to him of what tracks of the MP3 recording are played for different levels of dangerous situations (e.g. Track 1: approaching stationary forktruck; Track 2: forktruck approaching at high speed, etc.), and the user could then record warnings that are relevant or attention-getting to him. In this manner, a user is able to select warning words or speech inflections that would get his attention. For example, a user may choose to include his own name (perhaps shouted) in a warning track for an imminent danger, "JOHN SMITH--danger move NOW!" A colloquial analogy of this is how a parent can typically more easily command their child's attention by using their first, middle and last name. An endangered user should respond to urgent warnings with the same level of attention. In other examples, an employee's supervisor records the warning tracks--again with the idea being that a directive from a supervisor (even if recorded) might elicit a more effective response than an unfamiliar voice making the warning. An alternative to recording full warning tracks for every situation is to record individual words or phrases, and then to provide the user with the hardware and logic to be able to string these pieces together to form a relevant warning depending on the dangerous situation encountered. In an analogy to selecting one's ringtone on a mobile phone, a person could also be presented with a menu of canned or pre-recorded warnings, with the ability to select those that were the most attention-getting.
Another example threat communication mode with improved conspicuity disclosed herein is visual warnings. Rather than relying on wall or ceiling-mounted lights for area-generalized warnings, conspicuity is enhanced in these examples by visually-based threat communication being personalized to an individual who is threatened, or perhaps the source of the threat (a machine or an individual operating it). In the case of a personalized visual threat-communication, safety glasses are provided with an embedded source of light. A schematic view of an example pair of safety glasses 200 is shown in FIG. 12. Along the upper rims 210 of each eyepiece, a longitudinally-extending light source 220 is provided, such as a side-emitting fiber-optic cable. A source of light, such as a multi-color (for example, red and green) LED is carried elsewhere on the person, along with control electronics and a power source, such as a 12V battery--all represented schematically in functional box 230. Some or all of the contents of functional box 230 could be carried on the glasses (e.g. the LED'S), on the wearer, or even elsewhere. Depending on what components are where and what accompanying electronics are present, either wired or wireless connections among components could be used. The controls and glasses could be programmed to respond to various dangerous situations (as detected by any of the sensing and hazard discrimination techniques described above) by presenting light-signaling to the wearer of the glasses that is highly conspicuous by virtue of its proximity to the eye of the wearer. Different colors or other modulations of the light output from the fiber-optic cables 220 could be used to convey different threats or levels of danger to the user. These will be discussed in greater detail below. As an alternative to LED driven fiber-optic cable, the longitudinally-extending light source could also be a small array of LEDs.
Although the power consumption in terms of creating the visual warning and powering the processor necessary for such a complex warning are high, "heads-up" displays could also be incorporated into safety glasses as such displays are currently incorporated into the goggles used by military jet pilots. Such a heads-up display would actually project warning content in such as way so as to appear in front of the wearer. That warning content could be in the form of words, icons, symbols, etc. and could incorporate other features to enhance conspicuity such as colors, changes in intensity, and the like.
Another example of enhanced-conspicuity visual threat communication actually makes the potentially endangered pedestrian the source of the warning signal. In this example, when a dangerous condition is detected by a sensing and hazard discrimination system (such as a forktruck driving dangerously close to a pedestrian), some part of the pedestrian is illuminated. In the representative drawing shown in FIG. 13, not only does a light array 250 on the pedestrian's safety helmet H light up, but so do bracelets 260 on each of his arms. The intent is for the pedestrian to be a visual warning of the hazardous situation to the source of the hazard--the forktruck and its operator through the illumination of the lights. But since the pedestrian probably cannot see the light array on his helmet (unless perhaps the light signaling is also tied to his safety glasses as described above), the lights on the bracelets 260 on his arms are intended to also convey the potential danger to him in a conspicuous way.
Enhanced visual conspicuity threat communication can also be carried by the dangerous instrumentality--in this example a forktruck. The forktruck FT depicted in FIG. 14 includes a longitudinally-extending light source 300 on some or the entire lower perimeter of the vehicle. The light-source might be LED driven side-emitting fiber-optic cable, an array of LED's or any other suitable light source. Given that these lights are on a forktruck with access to a greater and more consistent power source, conventional light sources could also be used. In any event, the light source 300 is capable of providing visual warning to surrounding pedestrians by projecting light onto the floor surrounding the forktruck FT, as shown at 310. Under normal operating circumstances (where the sensing and hazard discrimination system does not detect a potentially hazardous situation), the projected light could be green. This is a visual indication to the forktruck operator that things in the vicinity of the forktruck are safe, and a visual indication to others in the facility (if in a line of sight where they can see the color) that a safe condition exists. Once a hazardous situation or potential is detected, the light array 300 projects a different color, for example, the color red. Again, this serves as a conspicuous visual indication to not only the forktruck driver, but also to potentially affected pedestrians in the vicinity. This light signal can also be modulated using techniques previously described. For example, the shape of a projected red light signal could be modulated by forktruck speed or turning status to be relatively larger in a direction of greater potential danger.
A communication mode that is related to tactile sensation is forktruck speed. If determination of a dangerous situation by a sensing and hazard discrimination system (e.g. a pedestrian in close proximity, passage of the forktruck through a doorway, a forktruck backing out of a trailer with a pedestrian in the loading dock vicinity) resulted in the speed of the forktruck being reduced (perhaps to zero), that reduction in speed would serve as a tactile indication to the forktruck driver of the dangerous condition. Interestingly, the reduction in speed could well serve as a visual warning to pedestrians in the vicinity that a dangerous condition existed--dangerous enough to cause an automatic speed reduction of the forktruck. Combining that reduction is speed with another mode or warning (e.g. an aural or light-based visual warning) could be even more effective.
Regardless of how such multi-mode warnings are implemented in hardware, the presence of multiple warning modes presents opportunities for enhancing the conspicuity of the warnings generated thereby. One enhancement is provided by how the various modes of warning are staged for the increasing severity of imminence of a threat. Low-level warnings (intended to raise awareness as opposed to empower action) can be provided by a first of the modes--for example tactile. The next level of warning (increased imminence of the dangerous situation) can be provided by a second mode--for example aural. Finally, the highest level of warning (for an imminent potentially catastrophic event like a collision) can be a third mode such as a visual warning. Appropriate training is provided to personnel to recognize the threat hierarchy represented by the various threat-communication modes: in this example vibration of tactile sources means "be aware," aural warnings mean "be prepared to take action," and visual warnings mean "take corrective or avoidive action immediately."
The conspicuity of threat communication is also enhanced by modulating the threat communication based on the imminence of the threat. Regardless of the mode (or modes) of threat-communication, the signal is modulated to convey a different signal as the threat imminence increases. An example of this in the context of an aural warning is volume. As the threat becomes more imminent, the volume of the warning increases. The pitch of an aural warning (whether a single tone, or a complex audio signal like speech) could also be modulated in this fashion. For a repeated aural warning, the periodicity of the repetition can be modulated to convey increasing threat imminence presumably with shorter cycles indicating more immediate danger. Rhythm could also be modulated for a multi-beat sound, for example with greater syncopation of the beat being indicative of a more imminent threat. Moreover, one or several of these forms of modulation could be combined to further enhance conspicuity. Supplying all of these modulation elements together could make the warning signal into something akin to a musical signal. A colloquial example of these various aural modulations combining to convey the rising imminence of a threat is the theme music to the film "Jaws". Tempo, rhythm, volume and pitch are all modulated to convey the danger of the shark drawing closer and finally striking. This music is clearly conspicuous to the listener, and using similar modulation techniques can make aural warnings in the industrial setting equally as conspicuous.
While the imminence of a threat is an aspect of the threat that can be specified in the warning(s) presented to the endangered person, additional aspects of the threat can also be conveyed to enhance threat communication. Several examples of threat-specified warnings will be presented below. One theme of threat-specified warnings is to provide enough information to the endangered person to empower that person (e.g. a pedestrian under threat of being struck by a forktruck) with adequate information about the nature of the threat so as to allow him the ability to exercise judgment in either avoiding the hazard or extricating himself from the dangerous condition. For the purposes of these examples, techniques based on aural (sound) communication will be presented. As show above, however, issuing warning communications in multiple modes (e.g. aural, visual and tactile) may be beneficial, and those additional kinds of warnings could also be employed to convey threat-specified warnings. Moreover, all of the examples related to warnings for the example "endangered person" of a threatened pedestrian could apply equally to other people involved in the situation, such as forktruck (or other vehicle) operators, bystanders, etc.
In the area of threat-specified aural warnings, improvement can be made to conventional warnings. Referring to the example of a pedestrian equipped with an RF receiver capable of receiving and decoding RF signals transmitted by a forktruck, a conventional system might provide some warning to the pedestrian when the signal strength rises above a certain threshold indicative of a dangerous proximity of the forktruck. Such a warning conveys only limited information, and may not be adequate to allow the pedestrian to take effective corrective or avoidive action. Rather, a more effective communication of that threat would convey something about its nature. For example, assume that either: 1) the forktruck has the ability to transmit an RF signal modulated by its state of movement (the transmitted signals are different when the forktruck is stationary versus when it is moving, and indicative of the speed and direction of the movement) or 2) that the receiver on the pedestrian has the ability to make such determinations based on the signal(s) received from the forktruck, or a combination of these functionalities. Under that assumed scenario, a threat-specified warning would provide different actual warning based on whether the forktruck was moving toward the pedestrian, or whether the forktruck was stationary and the pedestrian simply moved close enough to be within a proximity that would otherwise be dangerous if the forktruck were not stationary. For the less dangerous situation of a pedestrian moving close to a stationary forktruck, no warning might be given at all. Alternatively, a warning to raise the awareness of the pedestrian might be given since he is close to the forktruck and it might begin moving at any time. For a moving forktruck approaching dangerously close to a pedestrian, a higher level warning of imminent danger might be communicated. If the warnings are communicated to the pedestrian aurally, these different warnings (or indications of corrective action) for different levels of threat could be produced in a variety of ways. In one scenario, several warnings for several different threats have been recorded in some medium and are carried with the pedestrian. An example might be an MP3 player with prerecorded tracks. A unit capable of processing either signals sent from the forktruck modulated with threat-specific information or capable of translating unmodulated signals from the forktruck to determine the threat itself would also be capable of determining which warning should be conveyed to the pedestrian. Track 1 of the MP3 player might be "You are in dangerous proximity to a stopped forktruck--use caution", while track 2 might be "DANGER--Forktruck rapidly approaching--collision possible!" Depending on the threat-specific information determined by the processor, it would output a control command to the MP3 player to play the prerecorded track relevant to the determined danger. In other examples, a processor can be provided with a broad possible vocabulary (for example 50 or 100 words that could be used in warning in the context of interest), and logic for formulating warnings would string together such words depending upon the nature of the threat the processor determines. This would allow the specificity of the threat-warning to be increased, particularly for cases where more accurate and detailed threat information can be conveyed to the processor by the hazard sensing and/or locating systems described above. Moreover, the vocabulary could be dynamically modified over time to keep the warnings "fresh" to the listener.
Other types of threat-specified information can be conveyed to an endangered pedestrian besides the existence or specific nature of a threat, or the imminence of the danger. For a sensing/location system capable of determining imminence of a threat, the identity of the forktruck driver could be useful information to the endangered pedestrian. Rather than simply receiving a warning like "Forktruck approaching--collision possible", one could receive the warning "John Smith's forktruck approaching in 5 seconds". If experience tells the pedestrian that John Smith's safety record or driving habits are poor, the receipt of such threat-specific information may allow the pedestrian to take more effective or swift corrective action. Type of information conveyed in some examples include whether the forktruck is loaded or not. The sight lines for the driver of a loaded forktruck are much more limited than an unloaded truck, and knowing that the truck is loaded may again suggest to the pedestrian that he should treat the threat more seriously. Similarly, it could be useful to the pedestrian to know whether the forktruck was traveling in a forward or rearward direction. Again, the sight lines for a backing forktruck are much more limited than for a traveling forktruck, and this information might be relevant to an endangered pedestrian.
Another alternative for implementing direction or location specification to a warning signal is to provide a potentially threatened individual with multiple position indicators. Since indicators numbering beyond two might be problematic for our stereo senses (sight and sound), this example may be implemented in the tactile sense, since it is not subject to this limitation. Accordingly, a potentially threatened person is provided with four position indicators in the form of tactile stimulators, illustratively representing left, right, front and back. For a centralized hazard discrimination system capable of distinguishing the location of each of the four position indicators, a warning signal is formulated to only stimulate the indicator or indicators in closest proximity to the hazard. Returning to the south-facing pedestrian and the eastbound forktruck, the hazard discriminator would only stimulate the "right" indicator to indicate the approach vector of the threat. If, however, the forktruck were approaching from 315 degrees (toward 135 degrees), the hazard discriminator send a warning signal stimulating both the "right" and "back" sensors equally. For approach angles between 270 and 315, greater stimulation level might be provided to the "right" indicator than to the "back" indicator, assuming that the tactile sense can adequately distinguish such stimulation levels. Another option is to provide an array of stimulators around the perimeter of the pedestrian's body to be able to use the same approach to achieve greater angular specificity. As with the aural warning, the tactile warning might be modulated as the orientation of the pedestrian approaches the orientation of the threat.
A similar directionality can also be conveyed to the pedestrian even if there is not a centralized hazard discrimination system. In this example, the pedestrian carries the four tactile position indicators, but also carries a similarly-oriented array of four detectors. To provide warning signals, an approaching forktruck emits a repeating signal in a forward direction that can be detected by the four detectors on the pedestrian. Control electronics allow the repeating signal to be received by the four detectors, and resolved to determine the direction of approach of the forktruck. For example, if the pedestrian is facing north, the four detectors are facing the compass points. For a southbound forktruck, the north detector would detect the signal first, followed by a simultaneous detection by the east and west detectors, and finally followed by a detection by the south detector. For the same orientation of the pedestrian, a forktruck approaching on a 45 degree path (toward 225 degrees) would result in a simultaneous detection by the north and east detectors, followed by a simultaneous detection by the south and west detectors. In short, an operation could be programmed into the control electronics to be able to resolve the direction of the threat from any angle. In a similar vein, the control electronics could then control the tactile position indicators to convey the determined directionality to the affected pedestrian. In some examples, the four detectors have the same orientation as the four stimulators, and the control electronics are programmed to first determine the orientation of the threat, and then to stimulate either one or two stimulators to convey that threat orientation. In the case of a threat oriented from the north in our example, only the stimulator in that orientation is activated--but for the threat on a 45 degree vector, both the north and east stimulators are activated. This system has the benefit that it can be implemented without regard for the compass orientation of the pedestrian. If he is facing south instead of north in our example, his back and left stimulators are activated for a forktruck approaching on a 45 degree vector, as opposed to his right and front stimulators if here were facing north for the same forktruck approach. Moreover, the example is not limited to 4 detectors or stimulators, and more of either could improve accuracy.
The example system 1700 of FIG. 17 includes a processor 1712. For example, the processor 1712 can be implemented by one or more Intel.RTM. microprocessors from the Pentium.RTM. family, the Itanium.RTM. family or the XScale.RTM. family. Of course, other processors from other families are also appropriate.
In some examples, a method disclosed herein includes determining threat levels for hazards in a plurality of different zones within a building, classifying the threat levels into at least one of a first threat level and a second threat level, designating a first zone of the plurality of different zones having the first threat level with a first detectable indicator, and designating a second zone having the second threat level with a second detectable indicator.
In some examples, the method includes providing at least one of the first detectable indicator or the second detectable indicator as a color.
In some examples, at least one of the first detectable indicator or the second detectable indicator as a color includes coloring at least one of a flooring of the first zone having the first threat level with a first color or coloring a flooring of the second zone having the second threat level with a second color, the first color being different than the second color.
In some examples, the method includes providing at least one of the first detectable indicator or the second detectable indicator as the color includes using color lighting associated with at least one of the first zone having the first threat level or the second zone having the second threat level.
In some examples, the method includes providing a vehicle capable of moving between the first and second zones, the vehicle capable of detecting, via a detector, at least one of the first detectable indicator or second detectable indicator.
In some examples, the method includes detecting the first detectable indicator which is at least one of a first colored floor or a first colored light indicative of the first zone, or detecting the second detectable indicator which is as at least one of a second colored floor or a second colored light indicative of the second zone.
In some examples, the method includes modifying an operational parameter of the vehicle upon detection of at least one of the first detectable indicator or the second detectable indicator.
In some examples, the method includes modifying the operational parameter of the vehicle comprises at least one of limiting the vehicle to a first speed when the first detectable indicator is detected or limiting the vehicle to a second speed when the second detectable indicator is detected, the first speed being different than the second speed.
In some examples, a method for detection of hazards in different areas of a building includes assigning a first threat level for a hazard in a first area of the different areas, assigning a second threat level for a hazard in a second area of the different areas, the first threat level being different than the second threat level, employing a first detection system to detect the hazard in the first area assigned the first threat level, the first detection system having a first ability to detect the hazard in the first area, and employing a second detection system to detect the hazard in the second area assigned the second threat level, the second detection system having a second ability to detect the hazard in the second area, the first ability being different than the second ability.
In some examples, the method includes modifying, via the first detection system, an operational parameter of a vehicle based on the vehicle being in the first area.
In some examples, modifying the operational parameter of the vehicle includes limiting a speed of the vehicle in the first area.
In some examples, employing the first detection system includes monitoring, via the first detection system, the hazard in the first area.
In some examples, the method employing the second detection system comprises monitoring, via the second detection system, the hazard in the second area.
In some examples, the method includes assigning a first color to the first area having the first threat level and assigning a second color to the second area having the second threat level, the first color being different than the second color.
In some examples, the method includes distinguishing between the first color and the second color via at least one of the first detection system or the second detection system.
In some examples, the method includes adjusting the first threat level for the hazard in the first area of the different areas based on a dynamic characteristic of the first area.
In some examples, adjusting the dynamic characteristic is based on at least one of a population density, traffic density or a temporal characteristic in the first area.
In some examples, the method includes capturing the dynamic characteristic based on statistical analysis.
In some examples, statistical analysis includes monitoring the first area over a predefined period of time using at least one of a population density or a traffic density of the first area.
In some examples, monitoring the first area further includes monitoring the first area over a time-based period such as at least one or more workshifts to determine at least one of the population density or the traffic density of the first area.
In some examples, a method includes receiving an input relating to locations of a plurality of entities of interest, calculating a proximity between a first entity of interest of the plurality of entities of interest and a second entity of interest of the plurality of entities of interest, comparing the proximity between the first and second entities of interest to a plurality of thresholds, and determining a level of warning based on the comparison with the plurality of thresholds.
In some examples, the method includes providing the level of warning to at least one of the first entity of interest or the second entity of interest.
In some examples, receiving the input comprises receiving detailed location data relating to the pluralities of entities of interest.
In some examples, the method includes obtaining a facility layout from a database.
In some examples, the method includes determining whether an obstacle identified in the facility layout affects the determination of the level of warning.
In some examples, the method includes identifying a fixed obstacle from the facility layout and determining if the fixed obstacle is positioned between the first entity of interest and the second entity of interest.
In some examples, the method includes providing a warning to at least one of the first entity of interest or the second entity of interest if the fixed obstacle is not positioned between the first and second entities of interest.
In some examples, comparing the proximity to the plurality of thresholds includes comparing the proximity to a first threshold, a second threshold and a third threshold.
In some examples, determining the level of warning includes determining to continue monitoring the first and second entities of interest when the proximity is less than a first threshold.
In some examples, determining the level of warning includes providing an alarm when the proximity is less than a second threshold and greater than the first threshold.
In some examples, determining the level of warning includes at least one of preventing or reducing movement of at least one of the first entity of interest or the second entity of interest when the proximity is less than a third threshold and greater than the second threshold.
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