Patent Description:
Another type of optical detector is a chamber-less detector. In this approach, rather than the chamber, a light beam is emitted through an open volume, such as a room. A light sensor in the volume detects intensity of light and, similar to the aspirating detector, determines whether smoke is present based on changes in intensity. <CIT> discloses systems and method for adaptively controlling the illumination of a scene. In particular, a scene is illuminated, and light reflected from the scene is detected. Information regarding levels of light intensity received by different pixels of a multiple pixel detector, corresponding to different areas within a scene, and/or information regarding a range to an area within a scene, is received. <CIT> discloses use of one more emitted beams of radiation, for example, laser beam(s), in combination with an image capturing means, for example, one or more video cameras and/or optical elements to detect particles, for example smoke particles, located in an open space.

According to a first aspect of the invention there is provided a multi-point detection system as recited in claim <NUM>.

In a further embodiment of any of the foregoing embodiments, the light source includes one or more modulated light sources.

In a further embodiment of any of the foregoing embodiments, the detection nodes lie substantially in a single plane.

In a further embodiment of any of the foregoing embodiments, at least one of the light source and at least one of the one or more light sensors are configured with micro-lenses.

In a further embodiment of any of the foregoing embodiments, the one or more sensors is a single light sensor and a collimating lens array that defines the array of lines of view and focuses scattered light received along the lines of view onto the single light sensor.

In a further embodiment of any of the foregoing embodiments, the one or more sensors includes a plurality of collimated light sensors arranged to define the array of lines of view.

In a further embodiment of any of the foregoing embodiments, the controller is configured to determine a chemical identity of the target species from one or more of an amplitude of the process light, spectrum of the process light, and polarization of the process light over the range of wavelengths via the sensor signals.

There is also disclosed a multi-point detection system including one or more modulated light sources configured to emit an array of collimated light beams, and one or more light sensors define an array of lines of view. The lines of view intersect different ones of the collimated light beams at respective detection nodes. The one or more light sensors are operable to emit sensor signals responsive to received process light from interaction of the collimated light beams with an analyte at the detection nodes. A controller is connected to receive the sensor signals. The controller is configured to determine from the process light whether the analyte contains a target species, and determine distances of the detection nodes based on time-of-flight of the collimated light beams from the one or more light sources to the detection nodes and process light from the detection nodes to the one or more light sensors.

The controller may be configured to determine whether a cloud of the target species is moving and at what speed the cloud of the target species is moving.

The controller may be configured to determine that the cloud of the target species is moving by identifying at which detection nodes the target species is present at a first time, identifying at which detection nodes the target species is present at a second, later time, and identifying a pattern in which the species is present at one or more of the detection nodes at the second time but not the first time and in which the species was present at one or more of the detection nodes at the first time but not the second time.

The controller may be configured to estimate the speed at which the cloud of the target species is moving by identifying at which detection nodes the target species is present at a first time, identifying at which detection nodes the target species is present at a second, later time, identifying that the species is present at one of the detection nodes at the second time but not the first time, and estimating the speed based on a distance between the detection nodes and a time difference between the first time and the second time.

The controller may be configured to determine whether a cloud of the target species is changing in cloud size and at what rate the cloud size is changing.

The controller may be configured to determine that the cloud of the target species is changing in cloud size by identifying at which detection nodes the target species is present at a first time, identifying at which detection nodes the target species is present at a second, later time, and identifying a pattern in which the target species is present at one or more of the detection nodes at the second time but not the first time and in which the detection nodes for which the target species were present at the first time continue to be present at the second time.

The controller may be configured to determine the rate that the cloud size is changing by identifying at which detection nodes the target species is present at a first time, identifying at which detection nodes the target species is present at a second, later time, identifying that the species is present at one of the detection nodes at the second time but not the first time, and estimating the rate based on a distance between the detection nodes and a time difference between the first time and the second time.

According to a second aspect of the present invention there is provided a method as recited in claim <NUM>.

A further embodiment of any of the foregoing embodiments includes at least one of pulsing the collimated light beams, varying a pulse width of the collimated light beams, varying an inter-pulse interval of the collimated light beams, varying an amplitude of the collimated light beams, varying a frequency of the collimated light beams, or varying a polarization of the collimated light beams.

In a further embodiment of any of the foregoing embodiments, determining whether the target species is present in the analyte is based on an aggregate of the sensor signals from at least two of the detection nodes.

A further embodiment of any of the foregoing embodiments includes determining whether the target species is one or more of moving, spreading, and contracting based on the sensor signals.

A further embodiment of any of the foregoing embodiments includes changing operation of a heating, ventilation, and air conditioning system in response to determining that the target species is present.

A further embodiment of any of the foregoing embodiments includes determining whether there is a trend of increasing concentrations of the target species across two or more of the nodes and triggering an alarm if there is the trend.

A further embodiment of any of the foregoing embodiments includes determining a mean value and variance of a concentration of the target species across the nodes based on an aggregate distribution of the sensor signals and triggering an alarm if both the mean value and the variance increase.

<FIG> schematically illustrates a multi-point detection system <NUM> ("system <NUM>"). As will be appreciated from the examples herein, the system <NUM> can provide detection of a variety of chemicals and particles over a wide region, with enhanced characterization analytics.

The system <NUM> is disposed in a region in which an analyte (e.g., air) is to be monitored for one or more target species. Although not limited, the region may be a room and the analyte may be air circulating in the room. The system <NUM> may be used to determine the presence of target species in the analyte (and thus in the region), such as smoke, chemicals, and bio-agents, as well as identify the type of chemical(s) or agents in the analyte. Such information may then be used to identify threat situations and, if appropriate, trigger an alarm or other response.

The system <NUM> includes one or more light sources <NUM>, which may be mounted/affixed using fasteners or the like onto a support 21a (e.g., a wall, a ceiling, a corridor, a room, a building structure, etc.). The light source <NUM> utilizes a single light source or element 22a that emits light, represented at L1, to a lens element <NUM> of the light source <NUM>. The lens element <NUM> includes a plurality of lenses 24a that divide and collimate the light L1 into an array of collimated light beams <NUM>. Light sources <NUM> may emit light beams <NUM> in a single plane, in multiple planes, or in other three-dimensional pattern(s). Lenses 24a may be varied by controller <NUM>, e.g., as a variable attenuation to modulate the light intensity (amplitude) using a half-wave plate and a polarizer, and the like. Independently, Lenses 24a may be varied by controller <NUM>, e.g., as a variable polarization (as a liquid crystal polarization rotator). As used herein, an "array" is not restricted to a design having regular spacing in any dimension in some coordinate system, e.g., cartesian, polar, or the like. In specific, an array may have random position and orientation in 1D, 2D, or 3D.

The light source <NUM> may emit light over a range of wavelengths and/or frequencies. The light source 22a is a laser that emits a laser beam at a wavelength that is altered in a controlled manner across a range of wavelengths and range of pulse frequencies or other modulation in a controlled manner. For instance, light source <NUM> can scan the analyte across ranges of amplitudes, wavelengths (frequencies), polarizations, and/or pulse frequencies or timings. As used herein, "light" may refer to wavelengths in the visible spectrum, as well near infrared (NIR), midwave infrared (MWIR), longwave infrared (LWIR), near ultraviolet, and far ultraviolet, regions. In general, light source <NUM> may emit radiation at any frequency in the electromagnetic spectrum.

The system <NUM> also includes one or more light sensors <NUM>, which may also be mounted/affixed using fasteners or the like onto a support 21b (e.g., a wall, a ceiling, a corridor, a room, a building structure, etc.). In this example, the light sensor <NUM> utilizes a single light sensor or element 28a that receives focused light, represented at L2, from a lens element <NUM> of the light sensor <NUM>. The light sensor 28a may be a solid state sensor, such as but not limited to, a photosensor. Example photosensors may include photodiodes, bipolar phototransistors, photosensitive field-effect transistors, and the like.

The lens element <NUM> in this example includes a plurality of lenses 30a that define an array of lines of view <NUM>. A "line of view" is a straight path from a lens 30a along which the lens 30a can, to the exclusion of light from other directions, receive light from the region in which the system <NUM> is used. The lines of view <NUM> may lie in a single plane, in multiple planes, or in other three-dimensional pattern(s).

Each of the lines of view <NUM> intersect different ones of the collimated light beams <NUM> at respective detection nodes <NUM>, which in one non-limiting embodiment are half way between the light source <NUM> and the light sensor <NUM>. Each detection node <NUM> is a localized region in space at which a line of view <NUM> crosses a collimated light beam <NUM>. Since both the collimated light beam <NUM> and the line of view <NUM> have a two-dimensional cross-section, a detection node <NUM> may be substantially equal to the volume of the intersecting portions of the collimated light beam <NUM> and the line of view <NUM>. In one non-limiting example, the nodes <NUM> may lie substantially in a single plane and thus may constitute a "light curtain". This light curtain may be oriented substantially vertically, as in an outdoor application, where ambient winds might propel contaminants across the curtain. The light curtain may be oriented substantially horizontally, as in an indoor application, where heat release might propel a buoyant plume of contaminants across the curtain. In general, the light curtain may be oriented in any direction. The distribution of nodes <NUM> within a light curtain may be such that they can provide coverage to a much larger space than the sum of their individual sizes. In one non-limiting embodiment this may be done for smoke detection, where nodes <NUM> in a light curtain are less than <NUM> square foot and spaced <NUM> feet apart. In another non-limiting embodiment, each detection node <NUM> in a light curtain may be spaced about <NUM> square feet to about <NUM> square feet apart. In general, the nodes <NUM> may overlap, but alternatively some or all of the nodes may be spaced-apart to provide larger coverage.

In the illustrated example, both the array of collimated light beams <NUM> and the array of lines of view <NUM> are planar. The planar arrangements result in a linear configuration of the detection nodes <NUM> along axis A (<FIG>), which is also shown in an orthogonal view in <FIG>. For instance, to obtain the planar array, the lenses 24a of the lens element <NUM> have a linear configuration, as shown in the view of the lens element in <FIG>. The lenses 30a of lens element <NUM> proximal to the light sensor <NUM> can also have a linear configuration.

The configuration of the detection nodes <NUM> can alternatively be non-linear. For instance, <FIG> illustrates a lens element <NUM> that may be used in place of the lens element <NUM> in the light source <NUM>. The lens element <NUM> has lenses 124a arranged in a circular configuration. The lens element <NUM> and lenses 30a proximal to the light sensor <NUM> may also have a circular configuration. As a result of the circular arrays, the detection nodes <NUM> have a circular configuration as shown in <FIG>. The circular configuration can be used to cover a different expanse in the region in which the system <NUM> is used. As will be appreciated, the arrays could be arranged in many other configurations to generate configurations of the detection nodes <NUM> that are tailored to a particular region in which the system <NUM> is to be used or to a target area in the region which is to be monitored.

The analyte may circulate through the region in which the system <NUM> is implemented, including through the detection nodes <NUM>. If the analyte contains one or more target species, upon entering one of the detection nodes <NUM>, the target species may interact with the collimated light beam <NUM>, thereby causing a response, such as scattering of a portion of the light and/or absorption and emission of light (collectively "process light"). Some of the process light travels in the direction along the line of view <NUM> for that detection node <NUM> and is thus received into the corresponding lens 30a, which focuses the process light (focused light L2) to the light sensor 28a.

The light source <NUM> and light sensor <NUM> are electrically or optically connected at respective connections 40a, 40b for communication with a controller <NUM>, to control operation and receive feedback. It is to be understood that electrical and optical connections or communications herein can refer to direct connections, relayed connections, wire connections, wireless connections, or combinations of connections. The light sensor 28a is responsive to the received process light and is operable to emit sensor signals to the controller.

The controller <NUM> may include hardware (e.g., one or more microprocessors and memory), software, or both, that are configured (e.g., programmed) to carry out the functionalities described herein. In this example, the controller <NUM> is configured to determine from the process light whether the analyte contains a contaminant. The controller <NUM> determines whether a target species is present in the analyte based on an intensity of scattered light and the controller <NUM> determines a chemical identity of a species from a spectrum of the scattered light over the range of wavelengths. These two determinations may be referred to herein as, respectively, a presence determination and an identity determination.

The controller <NUM> can make a presence determination by analyzing the intensity of the sensor signals. In some instances, the sensor signals may be smaller than the ambient noise level in the sensed environment. In this case, controller <NUM> may correlate or convolve the sensor signals with a predetermined pattern where the predetermined pattern may be the light source modulation, or may be based on the light source modulation, to produce modified sensor signals which may then be used in presence determination and/or identity determination as the original sensor signals were. For instance, when no target species is present, the sensor signals are low. This may be considered to be a baseline or background signal, which can be distinguished from process light readings by the controller <NUM> pulsing the light source <NUM>. The pulses allow the controller <NUM> to determine a background or baseline based on light intensity detected by sensor 28a in between pulses, and remove that background from the sensor signals taken by sensor 28a during the pulsing. When a species is present and scatters or emits light, the sensor signals increase in comparison to the baseline signal. Higher concentrations of species produce more scattering or emission and a proportional increase in the sensor signal. An increase that exceeds a threshold may serve as an indication by the controller <NUM> that a species is present. The threshold may be predetermined, e.g., by experiments at the time the system <NUM> is commissioned, may be determined from light sensors <NUM> during operation, and may be adapted or vary with the signals from light sensors <NUM> over time.

The controller <NUM> can also make an identity determination by controlling the wavelengths emitted by the light source 22a and analyzing the sensor signals over the range of wavelengths of the collimated light beams <NUM>. For instance, the controller <NUM> scans the analyte over the range of wavelengths to collect temporal spectra of intensity versus wavelength (or equivalent unit). Different species respond differently with regard to absorbance and scattering of different wavelengths of light. Thus, the spectra of different types of species (taking into account a baseline or background spectra) differ and can be used as a signature to identify the type of species by comparison of the spectrum with a spectra library or database, which may be in the memory of the controller <NUM>. In this manner, the controller <NUM> can identify chemicals of interest, while also discriminating those chemicals from interference substances that are not of interest, such as dust, mold, pollen, or other incidental substances that may be in the analyte. Example chemicals that can be identified may include, but are not limited to, carbonyls, silanes, cyanates, carbon monoxide, and hydrocarbons, which may be present in toxic gases, aerosols, particulates, or mixtures of these.

Unlike a system that uses a single light beam, the system <NUM> enables monitoring across multiple points (i.e., the detection nodes <NUM>) of the region in which the system is implemented. This, in turn, provides additional analytic capabilities and monitoring over a larger expanse in the region than for a single light beam, which can only monitor a single point.

One analytic capability of the system <NUM> is the ability to determine distances of the detection nodes <NUM> based on time-of-flight of the collimated light beams <NUM> and process light received into the light sensor <NUM>. For example, the light source <NUM> may be pulsed at a set frequency controlled by the controller <NUM>. The controller <NUM> is programmed with the distances from the light source <NUM> to the respective detection nodes <NUM> and the distances from the detection nodes <NUM> to the light sensor <NUM>. For a given pulse, the time-of-flight for each of the collimated beams <NUM> to reach the corresponding detection nodes <NUM> can be calculated using the constant speed of light (approximately <NUM>/s) and the time-of-flight of process light from each of the detection nodes to the light sensor <NUM> can be calculated. Based on the timing of the pulse from the light source <NUM> and the time that the process light is received by the light sensor <NUM>, the controller <NUM> can identify which detection node <NUM> has detected a species. In one non-limiting embodiment, the light source <NUM>, its support 21a, light sensor <NUM>, and its support 21b are designed such that the respective times of flight to nodes <NUM> are unique and thus allow unambiguous identification of which detection node <NUM> has detected a species. Such a design may be achieved by solving an optimization problem where the variables are the design positions and angles and the objective function is the pathlength difference for all nodes <NUM> from source to sensor and the goal is to maximize the minimum difference.

In another non-limiting embodiment, if the five detection nodes <NUM> of the example in <FIG> are located at the distances as shown in Table <NUM> below, the total time-of-flight ("TOF") for a pulse of the collimated light beam <NUM> to reach each detection node <NUM>, scatter (if a contaminant is present at the node), and then reach the light sensor <NUM> can be calculated as total TOF (also shown in Table <NUM>). Thus, if the controller <NUM> receives sensor signals that are indicative of presence of a species, the controller <NUM> can determine from the timing which detection node or nodes <NUM> have the species. For instance, in the example shown in Table <NUM> if the sensor signals are received 40ns after a given pulse, the controller <NUM> determines that there is a species at detection node <NUM>. Likewise, signals at 60ns, 80ns, 120ns, and 160ns are indicative of respective nodes <NUM>, <NUM>, <NUM>, or <NUM>, respectively, having the species. Table <NUM> or similar tables may be saved in the memory of the controller <NUM> as a data set such as, for example, lookup tables.

The controller <NUM> can further be configured to determine whether the species is moving and at what speed the species is moving. For instance, referring to <FIG> which shows a representation of the detection nodes <NUM>, numbered <NUM>-<NUM> as from Table <NUM>, at Time A a contaminant cloud C envelops nodes <NUM> and <NUM>, but not nodes <NUM>, <NUM>, or <NUM>. The controller <NUM> identifies that at Time A there is contaminant species at nodes <NUM> and <NUM>. At Time B, represented in <FIG>, the controller <NUM> identifies that there is contaminant species at nodes <NUM> and <NUM>. Contaminant species is no longer identified at node <NUM>, and nodes <NUM> and <NUM> continue to have no contaminant species. The controller <NUM> compares the results at Time A and Time B, and identifies that contaminant species is no longer at node <NUM>, that contaminant species continues to be at node <NUM>, and that contaminant species is newly at node <NUM>. From this pattern, the controller <NUM> concludes that there is a cloud of contaminant species that is moving.

The controller <NUM> can also be configured to estimate at what the speed the cloud is moving. For instance, the controller <NUM> can determine the time difference between Time A and Time B. The controller <NUM> is also programmed with the distances between the nodes <NUM>-<NUM>. Here, based on the time difference and the distances between nodes <NUM> and <NUM>, the controller <NUM> calculates the speed of the cloud. As an example, if the time difference is <NUM> seconds and the distance from node <NUM> to <NUM> is <NUM> meters, the speed is <NUM> meters per second (approximately <NUM> miles per hour).

The controller <NUM> can also be configured to determine whether the cloud is changing in size. For instance, at Time A a contaminant species cloud C envelops nodes <NUM> and <NUM> as in <FIG>. At Time C, represented in <FIG>, the controller <NUM> identifies that there is contaminant species at nodes <NUM>, <NUM>, and <NUM>. The controller <NUM> compares the results at Time A and Time C, and identifies that contaminant species is newly at node <NUM> and that contaminant species continues to be at nodes <NUM> and <NUM>. From this pattern, the controller <NUM> concludes that there is a cloud of contaminant species that is expanding. Similarly, if the contaminant species is at fewer nodes at Time C than at Time A, the controller <NUM> concludes that the cloud is contracting.

The controller <NUM> can also be configured to determine the rate at which the size of the cloud is changing. Similar to the speed, based on the time difference and the distances between nodes, the controller <NUM> calculates the rate of change. As an example, if the time difference between Time A and Time C is <NUM> seconds and the distance from node <NUM> to <NUM> is <NUM> meters, the rate of expansion is <NUM> meters per second (approximately <NUM> miles per hour).

In another alternative light source <NUM> illustrated in <FIG>, the single light source 22a is used, but with the micro-lenses 124a directly on the single light source 22a. Here, micro-lenses 124a may be arranged in a linear or non-linear spacing on light source 22a. The surface of light source 22a may have a one, two, or three-dimensional topography.

<FIG> illustrates an alternate light sensor <NUM> that may be used in the system <NUM>. In this example, rather than the single light sensor 28a and lens element <NUM> there are multiple discrete light sensors 128a and multiple discrete micro-lenses 130a. Each microlens 130a is mounted on one of the light sensors 128a. The micro-lenses 130a define the array of lines of view <NUM>. Light sensors 128a with associated micro-lenses 130a may be arranged in a linear or non-linear spacing in one, two, or three dimensions.

In another alternative light sensor <NUM> illustrated in <FIG>, the single light sensor 28a is used, but with the micro-lenses 130a directly on the single light sensor 28a. Here, micro-lenses 130a may be arranged in a linear or non-linear spacing on light sensor 28a. The surface of light sensor 28a may have a one, two, or three-dimensional topography.

As will be appreciated, any of light sensors <NUM>, <NUM>, or <NUM> can be used in combination with any of light sources <NUM>, <NUM>, or <NUM>, and may be arranged linearly or nonlinearly as described above with respect to <FIG>. In addition, it is to be understood that one or more light sources <NUM>, <NUM>, or <NUM> may be used with one or more light sensors <NUM>, <NUM>, <NUM>. For instance, one or more collimated light beams <NUM> of light sources <NUM>, <NUM>, <NUM> may intersect lines of view <NUM> of two or more of the light sensors <NUM>, <NUM>, <NUM>, to increase the density of nodes <NUM>. In another example, collimated light beams <NUM> of different spectral colors may be used for selective detection. For instance, a collimated light beam <NUM> of one color may be effective for detecting species <NUM> but not species <NUM>, and a collimated light beam <NUM> of a different color may be effective for detecting species <NUM> but not species <NUM>. This establishes nodes <NUM> that are selective as to what kind of species they are screening for.

The following examples demonstrate control strategies of the system <NUM>. Unlike a single node or groups of nodes that more or less serve individually, the nodes <NUM> provide a group control strategy that may enhance early detection and threat event responsiveness.

In one example, the detectors <NUM> serve as a group, i.e., a detection network, to identify and track detected species. For instance, if one of the nodes <NUM> identifies a target species (e.g., smoke), in response the controller <NUM> may determine whether any other of the nodes <NUM> also have identified the target species. If no other node <NUM> identifies the target species, there is a low confidence level of the presence of the target species. As a result, the controller <NUM> may take no action or, depending on system alarm settings, may trigger a low level alarm. However, if one or more additional nodes <NUM> also identifies the target species, there is a higher confidence level that the target species is present. In response, the controller <NUM> may trigger an alarm and/or take responsive action. An example action is to command one or more changes in an HVAC system in the region in which the system <NUM> is used. For instance, dampers may be moved from open to closed states and/or fans and compressors may be deactivated, to reduce the ability of the target species to spread.

In a further example, the nodes <NUM> are used as a group to provide a two-prong detection strategy - one based on high concentration limits and another based on trending detection in the nodes <NUM>. In the first approach (high concentration), there is an alarm level for concentration of the target species at any one of the nodes <NUM>. If the level is exceeded at any one of the nodes <NUM>, the controller <NUM> triggers an alarm. For instance, the intensities of the sensor signals are representative of the concentration of the target species at the nodes <NUM>. The controller <NUM> statistically aggregates the sensor signals and produces a distribution across all of the nodes <NUM>. An alarm level for high concentration may be set with regard to a mean value of the distribution (e.g., the mean plus a multiple of the statistical standard deviation for the distribution). Thus, if the concentration of the target species at any one of the nodes <NUM> were to exceed the alarm limit, the controller <NUM> would trigger an alarm.

In the second approach (trending detection), the controller <NUM> looks for increases in concentration of the target species across two or more of the nodes <NUM>. In this approach a threat event is identified based on trending, but prior to the concentration reaching the high levels that would trigger the alarm under the high concentration approach as described elsewhere herein. For instance, controller <NUM> may identify an increase in concentration at one of the nodes <NUM> and, within a preset time period of that, identify an increase in concentration at one or more other nodes <NUM>. Thus, across a time period, the controller <NUM> identifies progressive increases in the number of the nodes <NUM> that have increasing concentrations. The time period may be varied, but in one example may be a relatively short time on the order of about one second to about <NUM> seconds, which is designed to address relatively rapidly unfolding/spreading threat events.

Upon identifying this progressive increase in the number of the nodes <NUM> that have increasing concentrations (but are below the high concentration alarm limit described elsewhere herein), the controller <NUM> may take no response, trigger a low level alarm, or trigger a high level alarm. In one example, the decision tree for this response is based on the number of nodes <NUM> that have increasing concentrations. For instance, if only a single node <NUM> has increasing concentration, the controller <NUM> takes no action. If two to four detectors have increasing concentrations, the controller <NUM> triggers a low level alarm. And if more than four nodes <NUM> have increasing concentrations, the controller <NUM> triggers a high level alarm. As will be appreciated, the numbers of nodes <NUM> that trigger these various responses can be varied, for example, depending upon the nature of the species detected, or other variables. In other words, the controller <NUM> can be configured or programmed to select a response that depends on the number of nodes <NUM> that have increasing concentrations that are under the alarm limit of the first approach from above.

There is an additional statistical approach that may be used with, or in place of, the high concentration or trending approaches described elsewhere herein. This statistical approach is somewhat similar to the trending approach in that it is also based on trending prior to the concentration reaching the high levels that would trigger the high concentration alarm. In this statistical approach the controller <NUM> looks for one or more particular trends over time in the mean value of the distribution taken from the statistical aggregate of the sensor signals of the nodes <NUM>. Most typically, the time period here would be longer than the time period above for the trending approach, as the approach here is intended to discriminate slow-moving events. For instance, the controller <NUM> identifies whether the mean and the variance of the distribution changes over time (e.g., over a period of more than <NUM> seconds up to several days or weeks) and, based on the outcomes, discriminates between different types of events.

The following scenarios demonstrate two examples of the statistical approach, the first of which is an event that is not a threat and the second of which is for a threat event. An increase in pollen in the air is an event that is not a threat, yet pollen may be detected and set off alarms in other systems that are not capable of identifying this type of event to avoid triggering an alarm (which would be a false indication of a threat). An increase in pollen levels may cause a slow increase in particulate concentration among the nodes <NUM>, which over the time period increases the mean value of the distribution. However, since pollen is pervasive in the air at all the nodes <NUM>, the variance of the distribution remains constant or changes very little over time. In this case, the controller <NUM> takes no responsive action.

<FIG> graphically depicts such an event and the affect to increase the mean value of the distribution. <FIG> shows distributions <NUM> and <NUM> of aggregate sensor output versus particulate concentration. The distribution <NUM> represents a no-threat condition, i.e., a background condition. The distribution <NUM> represents the aggregate at a later time and is shifted to the right compared to distribution <NUM>. The shift to the right indicates an increase in the mean value (at the peaks). The breadth of the distributions is representative of the variance. Here the variance of the distributions <NUM> and <NUM> is substantially identical, as both distributions <NUM> and <NUM> are relatively narrow, approximately bell-shaped curves.

The second scenario to demonstrate an example of the statistical approach relates to a slow-moving threat event. A slow-smoldering burning event or a bio-agent release may also cause a slow increase in particulate concentration among the nodes <NUM>. However, this type of event has a different effect on the distribution. Like the pollen, the particulate from the burning or the bio-agent increases the mean value of the distribution over the time period. But since the particulate emanates from the site of the smoldering or the bio-agent emanates from the point of release, the concentration among the nodes <NUM> is likely to differ. Nodes <NUM> that are closer to the site or release point are likely to have higher concentrations. As a result, not only does the mean value of the distribution increase, but the variance of the distribution <NUM> increases. In this case, the controller <NUM> triggers an alarm in response to identifying an increase in the mean value and an increase in the variance. In this manner, the controller <NUM> discriminates between harmless events, such as increases in pollen levels which increase the mean but do not change the variance of the distribution, and potential threat events, such as the smoldering burning or bio-agent dispersal which increase the mean and also increase the variance of the distribution.

<FIG> depicts an increase in the mean and the variance. <FIG> shows a distribution <NUM> of aggregate sensor output versus particulate concentration that is representative of a smoldering burning or bio-agent release event. The distribution <NUM> represents the aggregate at a later time than the distribution <NUM> (the background condition) and is shifted to the right compared to distribution <NUM>. The shift to the right indicates an increase in the mean value (at the peaks). The variance of the distributions <NUM> and <NUM> is substantially different, as distribution <NUM> is a narrow, approximately bell-shaped curve and the distribution <NUM> is a wide, approximately bell-shaped curve.

Also disclosed is a method for installing the system <NUM>. The method includes mounting the one or more light sources <NUM>, <NUM>, <NUM>, mounting the one or more light sensors <NUM>, <NUM>, <NUM>, and connecting the light sources <NUM>, <NUM>, <NUM> and the one or more light sensors <NUM>, <NUM>, <NUM> via connections 40a, 40b with the controller <NUM>. The light sources <NUM>, <NUM>, <NUM> and light sensors <NUM>, <NUM>, <NUM> may be mounted to the respective supports 21a, 21b. As an example, the light sources <NUM>, <NUM>, <NUM> and light sensors <NUM>, <NUM>, <NUM> may be mounted by fastening or securing the light sources <NUM>, <NUM>, <NUM> and light sensors <NUM>, <NUM>, <NUM> to the supports 21a, 21b. The installation may be part of an original installation in a building or other structure or part of a repair in which the system <NUM> is fully or partially replaced with new or repaired components. The installation may also include properly aligning the light sources <NUM>, <NUM>, <NUM> and the one or more light sensors <NUM>, <NUM>, <NUM> so that the collimated light beams <NUM> and the lines of view <NUM> intersect to generate the nodes <NUM>. As an example, the array of light sources <NUM>, <NUM>, <NUM> and the array of the one or more light sensors <NUM>, <NUM>, <NUM> may be arranged at a fixed angle relative to one another. For instance, the arrays may be orthogonally arranged, but other angles could alternatively be used. An orthogonal arrangement may be used when a spacing between the light sources <NUM>, <NUM>, <NUM> and the one or more light sensors <NUM>, <NUM>, <NUM> is three meters or more. In another example, the light sources <NUM>, <NUM>, <NUM> and the one or more light sensors <NUM>, <NUM>, <NUM> are closer than three meters, but are not orthogonal.

Claim 1:
A multi-point detection system comprising:
a light source (<NUM>; <NUM>; <NUM>) configured to emit an array of collimated light beams (<NUM>);
one or more light sensors (<NUM>; <NUM>; <NUM>) defining an array of lines of view (<NUM>), each of the lines of view (<NUM>) being a straight path from a lens (30a; 130a) along which the lens (30a; 130a), to the exclusion of light from other directions, receives light from the region in which the system is used, each of the lines of view (<NUM>) intersecting different ones of the collimated light beams (<NUM>) at respective detection nodes (<NUM>), the one or more light sensors (<NUM>) operable to emit sensor signals responsive to received process light from interaction of the collimated light beams (<NUM>) with an analyte at the detection nodes (<NUM>); and
a controller (<NUM>) connected to receive the sensor signals, the controller (<NUM>) configured to determine from the process light whether the analyte contains a target species; characterised in that
the light source (<NUM>; <NUM>; <NUM>) comprises a laser configured to emit a laser beam to a lens element (<NUM>) at a wavelength configured to be altered in a controlled manner across a range of wavelengths, the lens element (<NUM>) including a plurality of lenses (24a) that divide and collimate the laser beam into the array of collimated light beams (<NUM>); and in that
the controller (<NUM>) is configured to determine a chemical identity of the target species from a spectrum of scattered light over the range of wavelengths.