Patent Abstract:
One or more sensors gather data, one or more processors analyze the data, and one or more indicators notify a user if the data represent an event that requires a response. One or more of the sensors and/or the indicators is a wearable device for wireless communication. Optionally, other components may be vehicle-mounted or deployed on-site. The components form an ad-hoc network enabling users to keep track of each other in challenging environments where traditional communication may be impossible, unreliable, or inadvisable. The sensors, processors, and indicators may be linked and activated manually or they may be linked and activated automatically when they come within a threshold proximity or when a user does a triggering action, such as exiting a vehicle. The processors distinguish extremely urgent events requiring an immediate response from less-urgent events that can wait longer for response, routing and timing the responses accordingly.

Full Description:
RELATED APPLICATIONS 
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     FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT 
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     APPENDICES 
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     FIELD 
     Related fields include wearable electronics, and more particularly the formation of temporary ad-hoc communication networks including wearable electronics. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a conceptual map of an example of an ad-hoc network. 
         FIG. 2  is a block diagram of an example of an ad-hoc network. 
       The main components are sensors (input transducers), indicators (output transducers), and an intelligent agent that may include hardware, software, or both in a processor or in a group of distributed processors. The intelligent agent analyzes the sensor inputs, classifies them according to urgency and need for outside data, decides which indicators need to respond to the sensor inputs and how the signals are to be routed. 
       “Sensors” is used here is a generic term for all the input transducers transmitting signals to one or more processors. Sensors include cameras and microphones as well as biometric and environmental sensors. On-body sensors  202  include wearables (clothing  212  and mounted directly to the body with adhesive  232 ), hand-held or carried in backpacks or pockets while operating (accessories  222 ). Off-body sensors  204  may include anything not worn or carried by a user while operating. Off-body sensors may include sensors mounted on a vehicle  214 , on equipment are tools not carried during operation  224 , or in some embodiments the sensors worn or carried by another user  234 . 
       In some embodiments, the incoming information from all the sensors is synchronized in step  242  and recorded to storage in step  244 . The recordings may be transmitted in real-time to a server, or they may be stored for later upload. 
       The incoming information for all the sensors also goes to the intelligent agent  252 , and may be synchronized or not depending on the embodiment. In the intelligent agent  252 , a signal recognition engine  254  compares the incoming signals with examples of predicted signals stored in an event/response database  258 . If a match is found, intelligent agent  252  infers that the corresponding event has happened. Some embodiments may cross-check numerous sensors to prevent “false alarm” inferences. To formulate a response to the inferred event, the intelligent agent may use data from teammate/contact database  256 , which may use the location and type of inferred event, sometimes along with the identity of the user originate in the sensor signals, to decide who needs to be notified of the inferred event; partners, supervisors, medics, etc. 
       A procedural template database  262  may be included as a reference for any strict, complex, or frequently changed procedures that users must follow even in a chaotic environment, such as clean forensic practices, chain-of-custody handling of evidence, or emergency first aid for specialized situations. Some embodiments of the intelligent agent  252  may make use of other internal databases  264 ; for example, if the users are SCUBA divers, there may be an internal database  264  to calculate how much longer each diver may stay submerged and what kind of decompression stop, if any, is needed. In some embodiments, the intelligent agent may dry information from external or remote databases  272 , such as facial and voice recognition databases and criminal record databases. 
       If the signal recognition engine  254  infers an event that needs an immediate response, the prescribed command from event/response database  258  is sent directly over the local ad-hoc network to the prescribed indicator. The indicators may be visual, such as LEDs or the screens of smart watches or heads-up displays; audible, from variable tones to recorded instructions (e.g., from procedural template database  262 ); or tactile, such as haptic transducers. Like the sensors, there may be a group of on-body indicators  206  on clothing  216 , accessories  226 , or attached to the body by adhesive  236 . There may also be a group of off-body indicators  208  mounted on or in a vehicle  218 , tools are equipment  228 , or someone else&#39;s body  238 . In some embodiments, the intelligent agent may use location sensors to determine whether any of the users are close enough to make use of an off-body indicator. 
         FIG. 3  is a flowchart of data handling by a processor connected to an ad-hoc network. 
         FIGS. 4A-B  illustrate an example of a holster interlock sensor for an ad-hoc network of armed professionals. 
         FIGS. 5A-K  illustrate examples of wearable articles incorporating sensors or indicators. 
         FIGS. 6A-D  illustrate an example of an ad-hoc network for police work. 
         FIG. 7  is a flowchart of an example of a procedural-guidance function. 
     
    
    
     DETAILED DESCRIPTION 
     A team of workers performing a hazardous, unpredictable task can mitigate some of the risk by leveraging “safety in numbers,” coming to the aid of any teammate that finds himself or herself in trouble. Being able to help hinges on knowing what and where the trouble is as soon as it starts. This can be difficult if the teammates are too far apart to see or hear each other and normal communications (e.g., walkie-talkies, earbuds, cell phones, speaking and listening hardware built into protective gear) are not working. The area may be too noisy, or it may lack a repeater or other necessary infrastructure. The trouble may be of a kind that prevents the victim from communicating clearly: being overcome by toxic fumes, falling from a crumbling cliff-edge, or being ambushed by enemy combatants. Therefore, a need exists for a way to monitor teammates&#39; situations in real time without needing to converse over a conventional channel. Such a solution could be applied to war, anti-terrorist action, police and security work, firefighting, toxic-waste cleanup, disaster relief, search and rescue, and similar activities. 
     An ad-hoc network including wearable electronics worn on users&#39; bodies, and optionally including other components mounted on vehicles or temporarily set up at the task site, alerts other on-site (and optionally off-site) users when any user appears to need backup. For example, one or more wearable accelerometers may detect when the wearer falls or begins running. Wearable heart rate (HR) or galvanic skin response (GSR) sensors may detect surprise, strong emotion, or the onset of exhaustion. Wearable temperature and humidity sensors may warn when exposure to the environment becomes dangerous. Weapon holster interlocks may inform other users when any user draws a weapon. Microphones can produce audio data for voice stress analysis and voice recognition of users and other people that the users encounter, or sounds characteristic of environmental hazards such as flash floods or rockfall. Cameras may collect data for facial recognition or monitor activity in users&#39; blind spots. If input from multiple sensors is aggregated, synchronized using time-stamps, and recorded, a multi-perspective record of events can be produced. 
       FIG. 1  is a conceptual map of an example of an ad-hoc network. Police officers  102  and  104  are looking for missing hiker  122 . At the trailhead, they park their vehicle  106  and set off on foot. Each of the officers  102  and  104  has a wearable electronics with capabilities including transmission T and reception R. Transmission T and reception R may use any suitable communication protocol. 
     Vehicle  106  as capabilities that also include transmission T and reception R; either or both officers  102  and  104  may communicate with the vehicle at any time. This expands the officers&#39; capabilities while keeping their wearables simple, rugged, and lightweight with low power consumption, extending battery life and increasing the usefulness of portable chargers such as solar and hand-cranked chargers. For example, vehicle  106  may be able to relay messages from officers  102  and  104  to their dispatcher or to other police or park rangers in the area. The vehicle  106  may contain processors and on-board databases or links to databases in cloud  110 . 
     Optionally, a communication hub may be brought to the site, or an existing on-site communication hub may be redeployed as part of the a-hoc network. For example, a portable signal booster  108  may be carried in and set up if some feature of the terrain, such as the crest of a hill, attenuates communication between the officers  102 ,  104  and/or the vehicle. In rescue or emergency communication situations where target  122  wants to be found, portable signal booster  108  may enable officers  102 ,  104  to reach the mobile phone  124  of target  122 , or scan for a locator chip in mobile phone  124 , where previously the signals were too weak because the nearest cellular towers were too far away. Portable signal booster  108  may also enable the officers&#39; wearables to communicate with servers in cloud  110  directly. 
     Officers  102  and  104  may split up to cover more area, knowing that if they encounter threats such as unfriendly animal  114  or human fugitive  116 , their partner will be notified instantly. In some embodiments, the officers need not be able to give accurate directions or even to speak, because their wearable transmitters may react to the readings of stress-level sensors and motion sensors by transmitting a distress signal after such triggers as a rapid increase in heart rate, a rapid increase in perspiration, or beginning to run, jump, or fall. Their wearable receivers&#39; output may include a distance to the source of the distress signal, a direction from which the stress signal is coming, and the strength of the distressed person&#39;s reaction. 
     Embodiments of processors in the vehicle  106 , the portable signal booster  108 , and in some embodiments integrated with the wearables of officers  102 ,  104 , may distinguish urgent messages from non-urgent received messages, or messages that require the use of a database from those that do not, and route them differently as appropriate. Distress signals and other urgent messages may be immediately circulated through the local ad-hoc network formed between the officers&#39; wearables and optionally including one or more on-site vehicles and one or more deployed portable signal boosters. Such messages may simultaneously be sent to a dispatcher or to other officers in the area. Non-urgent messages may be sent to one or more cloud servers for retransmission with or without further processing. Optionally, the processor may record all the incoming signals from the officers&#39; wearable and other equipment to thoroughly document the operation. Such recordings may be archived on the fly or after the officers&#39; return. 
     As well as in search-and-rescue operations, the usefulness of these ad-hoc networks with wearables is readily adaptable to firefighting, criminal apprehension, warfare, disaster relief, mountain or cave exploration, undersea diving, in-habitat study of dangerous animals, and other activities where teams of users may face unpredictable hazards while not remaining visible to each other, where conventional communication may be difficult, or we&#39;re hazards may emerge too quickly to rely on conventional communications. 
       FIG. 2  is a block diagram of an example of an ad-hoc network. The main components are sensors (input transducers), indicators (output transducers), and an intelligent agent that may include hardware, software, or both in a processor or in a group of distributed processors. The intelligent agent analyzes the sensor inputs, classifies them according to urgency and need for outside data, decides which indicators need to respond to the sensor inputs and how the signals are to be routed. 
     “Sensors” is used here is a generic term for all the input transducers transmitting signals to one or more processors. Sensors include cameras and microphones as well as biometric and environmental sensors. On-body sensors  202  include wearables (clothing  212  and mounted directly to the body with adhesive  232 ), hand-held or carried in backpacks or pockets while operating (accessories  222 ). Off-body sensors  204  may include anything not worn or carried by a user while operating. Off-body sensors may include sensors mounted on a vehicle  214 , on equipment are tools not carried during operation  224 , or in some embodiments the sensors worn or carried by another user  234 . 
     In some embodiments, the incoming information from all the sensors is synchronized in step  242  and recorded to storage in step  244 . The recordings may be transmitted in real-time to a server, or they may be stored for later upload. 
     The incoming information for all the sensors also goes to the intelligent agent  252 , and may be synchronized or not depending on the embodiment. In the intelligent agent  252 , a signal recognition engine  254  compares the incoming signals with examples of predicted signals stored in an event/response database  258 . If a match is found, intelligent agent  252  infers that the corresponding event has happened. Some embodiments may cross-check numerous sensors to prevent “false alarm” inferences. To formulate a response to the inferred event, the intelligent agent may use data from teammate/contact database  256 , which may use the location and type of inferred event, sometimes along with the identity of the user originate in the sensor signals, to decide who needs to be notified of the inferred event; partners, supervisors, medics, etc. 
     A procedural template database  262  may be included as a reference for any strict, complex, or frequently changed procedures that users must follow even in a chaotic environment, such as clean forensic practices, chain-of-custody handling of evidence, or emergency first aid for specialized situations. Some embodiments of the intelligent agent  252  may make use of other internal databases  264 ; for example, if the users are SCUBA divers, there may be an internal database  264  to calculate how much longer each diver may stay submerged and what kind of decompression stop, if any, is needed. In some embodiments, the intelligent agent may dry information from external or remote databases  272 , such as facial and voice recognition databases and criminal record databases. 
     If the signal recognition engine  254  infers an event that needs an immediate response, the prescribed command from event/response database  258  is sent directly over the local ad-hoc network to the prescribed indicator. The indicators may be visual, such as LEDs or the screens of smart watches or heads-up displays; audible, from variable tones to recorded instructions (e.g., from procedural template database  262 ); or tactile, such as haptic transducers. Like the sensors, there may be a group of on-body indicators  206  on clothing  216 , accessories  226 , or attached to the body by adhesive  236 . There may also be a group of off-body indicators  208  mounted on or in a vehicle  218 , tools are equipment  228 , or someone else&#39;s body  238 . In some embodiments, the intelligent agent may use location sensors to determine whether any of the users are close enough to make use of an off-body indicator. 
       FIG. 3  is a flowchart of data handling by a processor connected to an ad-hoc network. The “on” trigger  302  that starts the system may be manual and user-operated, or maybe triggered by some action that indicates that the user is joining an ad-hoc network. For example, a police vehicle could have an infrared path across the doorway, similar to the obstacle detector that keeps an automatic door from closing if something is in the path. Whenever the police officer left the vehicle, e.g., for a traffic stop, crossing the infrared beam would automatically turn on the officer&#39;s wearable system and the vehicle system as step  304 . Alternatively, a proximity sensor in the vehicle could turn on the systems for step  304  when the officer&#39;s body moves out of a certain range. 
     Some embodiments with automatic “on” triggers  302  may provide for user override  306 , which triggers sensor deactivation  308 . For example, if a police officer leaves the vehicle to work on reports at the station or take a lunch break, it is highly unlikely that the ad-hoc network will be needed; nor will 2 hours of recorded typing be worth the data storage space it occupies. 
     If the sensors are activated and there is no user override, the user&#39;s wearable electronics connect to other local devices, any local processors, and optionally to a remote processor in step  310 . The processors commence monitoring the received sensor signals in step  312 . The signals are compared to entries in the local event/reaction database  314  and if a match is found at decision  316 , the urgency level is evaluated at decision  318 . For example, even if the sensors a single microphone, the intelligent agent may analyze the amount of voice stress and infer a degree of urgency from the result. The lowest urgency events may simply be stored to processor later time in step  328 . The highest urgency events will immediately activate a local indicator through the ad-hoc network, “jumping the queue” to precede or even interrupt less-urgent signals. Events of medium urgency (including high-urgency events that have already been broadcast over the ad-hoc network, and requests that involve querying one or more off-site databases) are relayed to a remote processor, e.g., a cloud-based processor, for processing: consulting the database, contacting dispatchers or other nearby officers, or other tasks that present no risks by being sent to the remote processor. 
     Not all signals that come two decisions  316  will match events in the event/response database. Some signals may be data transmitted from a remote processor in step  320 , including answers to medium-urgency queries. Those signals are relayed to the local indicators in the ad-hoc network whenever the system is not occupied by higher-urgency signals. If the signal does not match inferred event and is not data coming from a remote processor, the intelligent agents ignores it and continues to monitor the sensor signals, in effect looking back to step  312 . At any time, there may be an “off” trigger at decision  330  deactivating the system to save power when the ad-hoc network is not needed. Like the “on” trigger, the “off” trigger may be manual or automatic. 
       FIGS. 4A-B  illustrate an example of a holster interlock sensor for an ad-hoc network of armed professionals. When a soldier, police officer, or other security specialist draws a weapon during an operation, it almost always signifies an emergency need for backup. If removing a weapon from a holster automatically sends a high-urgency signal over an ad-hoc network, the user&#39;s allies in the area will be alerted immediately, even if the user is out of their sight or the environment is too noisy to hear what the user is saying. In some embodiments, removing the weapon from a holster may activate a wearable camera (e.g., mounted on a cap or near the neckline of a body-armor vest) to record what the user is seeing and/or a microphone to record what the user hears and says. This an example of sensors temporarily acting as indicators when they are turned on in response to signals from other sensors. 
     In  FIG. 4A , handgun  402  is secured in holster  404 . There may be a proximity sensor  414  in holster  404 , an accelerometer  412  on handgun  402 , or both to provide redundancy and reduce the incidence of false alarms. In  FIG. 4B , when handgun  402  is removed from holster  404 , accelerometer  412  senses the motion and sends a first signal  422  over the ad-hoc network. In addition, proximity sensor  414  in holster  404  stops sensing handgun  402  nearby and sends a second signal  424  over the ad-hoc network. 
     Although a handgun is the illustrated example, similar sensors could be mounted to nightsticks, stun guns, Tasers™, pepper-spray canisters, or other hand-held weapons. 
       FIGS. 5A-K  illustrate examples of wearable articles incorporating sensors or indicators. Some may have both sensors  502  and indicators  504 , or multiple sensor or indicator units. For example, an article that encircles some part of the body such as a watchband, hatband, glove, collar, shoe, or belt may hold a ring of haptic transducers indicating a direction to travel by activating the transducer facing that direction. 
     In  FIG. 5A , sensors  502  and/or indicators  504  may be mounted on the band, bezel, or strap of smart-watch  506 . In  FIG. 5B , sensors  502  and/or indicators  504  may be mounted on the brim or crown of cap  516 . In  FIG. 5C , sensors  502  and/or indicators  504  may be mounted on the outside or inside of glove  526 . In  FIG. 5D , sensors  502  and/or indicators  504  may be mounted on the outside or inside of body-armor  536 . 
     In  FIG. 5E , sensors  502  and/or indicators  504  may be mounted on the outside or inside of work shirt  546 . In  FIG. 5F , sensors  502  and/or indicators  504  may be mounted on the upper of work boot  556 . In  FIG. 5G , sensors  502  and/or indicators  504  may be mounted on the strap or buckle of belt  566 . In  FIG. 5H , sensors  502  and/or indicators  504  may be mounted on the pendant, cord, or clasp of lanyard  576 . 
     In  FIG. 5I , sensors  502  and/or indicators  504  may be mounted on the outside or inside of service-animal collar  586 . In  FIG. 5J , sensors  502  and/or indicators  504  may be mounted on the inward- or outward-facing services of a removable clip  596 . 1  and  596 . 2 . In  FIG. 5K , sensors  502  and/or indicators  504  may be mounted on a removable adhesive patch  598  to be worn temporarily on the surface of the skin. The adhesive embodiment may be convenient for sensors such as galvanic skin response (GSR) that need to maintain contact with the skin on a user in vigorous or nearly constant motion. 
       FIGS. 6A-D  illustrate an example of an ad-hoc network for police work. In  FIG. 6A , police officer  602  and partner  604  are patrolling in a vehicle  606  with an automatic on-trigger  608  for the officers&#39; wearable electronics. In  FIG. 6B , the officers have detained a suspect vehicle  626  carrying a driver  624  and a passenger  622 . Officer  602  has exited from vehicle  606 , automatically activating her wearable location sensor  618 . 
     In  FIG. 6C , officer  602  comes to the driver&#39;s window of suspect vehicle  626  to speak to the driver. In officer  602 &#39;s blind spot, passenger  622  leaves vehicle  626  at a run. Although officer  602  may not have seen it, a camera on police vehicle  606  had an excellent view. The intelligent agent reading the camera signal recognizes the event of the passenger leaving a detained vehicle and immediately send signal  610  over the ad-hoc network to or more of officer  602 &#39;s wearable indicators. For example, a warning LED under the brim of the officer&#39;s cap may illuminate; a haptic transducer on the officer&#39;s belt facing the direction of the fleeing passenger may buzz; or a heads-up display built into the officers&#39; eyewear may give more detailed information. 
     In  FIG. 6D , the timely-alerted officer  602  chases the suspect passenger  622 . The ad-hoc network stretches to wherever officer  602  goes. Her location sensor  618  allows her partner or other backup to join the chase from another direction, and biometric sensors  628  monitor her levels of stress and exertion as urgency indicators. 
       FIG. 7  is a flowchart of an example of a procedural-guidance function. Procedural steps can be difficult to remember if the procedure is new, or new to the person executing it; if the procedure is complex, seldom used, or has recently changed. Nevertheless, much can be put at risk by skipping a step of a procedure or doing it wrong. Evidence, or entire cases, may be thrown out of court. A patient may die or be permanently injured. A piece of military machinery may malfunction in battle. Therefore, a need exists to more reliably ensure that procedures are done correctly. 
     Ad-hoc networks including wearable sensors and/or indicators that enable prompts for the various stages of a procedure as is being performed. At step  702 , a sensor detects a procedure trigger. For example, a microphone may receive a police officer&#39;s voice saying the words “You&#39;re under arrest.” The intelligent agent infers the event of a suspect being arrested. In step  704 , it searches the procedure database (or other data-store)  703  for arrest procedures and retrieves the latest (for example including Miranda warnings). Periodically, step  705  updates the stored procedures. In step  706 , the steps of the procedure are visually displayed (or may be audibly recited) to the user executing the procedure. In some embodiments, the sensors look or listen for cues that a step has been performed (for example, by analyzing a filled-out form through a camera. Optionally, the execution of the procedure may be recorded to storage in step  708 . 
     The preceding Description and accompanying Drawings describe examples of embodiments in some detail to aid understanding. However, the scope of the claims may also include equivalents, permutations, and combinations that are not explicitly described herein.

Technology Classification (CPC): 7