GB2609638A - Method and system for managing environment - Google Patents

Abstract

A method 100 and a system for managing an environment is provided. The method 100 comprises receiving from a long-range transceiver device 102 and from a plurality of short-range transceiver devices 104 installed in the environment, information related to change in state of long-range signals and short-range signals, respectively; determining propagation characteristics of the long-range signals and the short-range signals 106; determine a current location and a current state of at least one of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals 108; communicating the current location and the current state for each of the one or more objects in the environment to an environment management system 110; and configuring the environment management system to adapt operations parameters of the environment 112.

Description

METHOD AND SYSTEM FOR MANAGING ENVIRONMENT

TECHNICAL FIELD

The present disclosure relates to a method and system for managing an environment, and in particular to a method and system for managing an environment based on non-intrusive and privacy aware occupancy monitoring.

BACKGROUND

In recent times, the increasing energy costs and environmental concerns including carbon emissions have raised the focus of industries towards transforming workspaces into energy-efficient and sustainable buildings. Also, various building regulations and policy frameworks require limited energy consumption and carbon emission levels of the buildings. Building regulations are moving towards a point where optimizing operational energy has become a requirement. Particularly, as a result of COVID-19, there has been an increased need to determine occupant density, movement, and proximity within workspaces or buildings to ensure that the occupants or persons can work at a safe distance from one another without posing a transmission risk. Most workspaces are designed to operate at a certain occupant density (such as, 1 person per 10 square meters) and thus to maximize the number of people who can return to work safely; the activity and presence of the occupants in and around the workspace is required to be monitored.

Beneficially, reducing energy usage by tracking occupants' movements and optimizing energy consumption reduces both direct and indirect energy usage and greenhouse emissions. For example, residential and business sectors contribute to 30% of total UK greenhouse gas emissions. This has created a demand for Building Management Systems (BMS) and other similar systems implemented in the workspaces for better space utilization, optimizing the impact of flexible working on workers' productivity and so forth. Such systems provide means for calibration and optimization of buildings in use to provide improved design measures and recommendations and further provides benefits associated with maximization of occupancy in a particular building. Notably, to achieve proper results, such systems require real-time and constant monitoring of the occupants of the building. The key challenge is to detect the occupancy with maximum accuracy at a low cost with high scalability, without any direct involvement of the occupants and at the same time preserving the occupant's privacy.

Conventionally, to perform such a monitoring, there exists some solutions, one of which requires direct involvement of target users e.g., wearing a tag or running a mobile application on their mobile phones. These solutions are mostly used for indoor wayfinding and proximity marketing and popularly adopted at airports, shopping malls, stadiums and so forth working on their own developed applications. Moreover, there are other solutions which do not require any direct involvement of target users. These solutions are popular for visitors tracking or counting, optimising flow, and managing indoor traffic. These solutions provide a non-intrusive tool to building owners to monitor people's presence. However, most of these solutions are costly, require infrastructure, and some of them that use cameras further raise serious privacy concerns. Further, an alternative approach is based on MAC address sniffing by WiFi access points and/or Bluetooth modules, wherein MAC addresses of the mobile device of the occupant in the vicinity of the sniffing sensor is captured to localise the user. However, such methods are unable to detect the activities of the occupants. There are also some WiFi based solutions known in the market for activity monitoring. However, since these solutions are designed for larger areas e.g., WiFi based-solution may cover an area of 900 square meters, the resulted warning system may be frequently contaminated with false-positive errors, which deteriorates the user's acceptance and inhibits them to make efficient use of their indoor facilities.

To overcome the aforementioned problems, the present disclosure provides a solution for nonintrusive and privacy-aware occupancy monitoring, which accurately detects the number of occupants and their activities, and thus helps with improving sustainability, security, safety, and reducing indoor energy consumption.

SUMMARY

In one aspect, the present disclosure provides a method for managing an environment, the method comprising: - receiving, by a processing arrangement, from a long-range transceiver device associated with the environment, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment; - receiving, by the processing arrangement, from a plurality of short-range transceiver devices installed in the environment, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment; - determining, by the processing arrangement, propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state for short -range signals, respectively; - determining, by the processing arrangement, a current location and a current state of at least one of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals, the current state being either a motion state or a stationary state; and - communicating, by the processing arrangement, the current location and the current state for each of the one or more objects in the environment to an environment management system; and - configuring the environment management system to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein.

In an additional embodiment, the long-range transceiver device comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices comprises a plurality of Bluetooth® Low Energy (BLE) sensors.

In an additional embodiment, determining the propagation characteristics of the long-range signals comprises determining, by the processing arrangement, a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby.

In an additional embodiment, determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement, a Channel State Information (CSI) of the short-range signals by measuring change in at least one of strength and wave characteristics of the short-range signals.

In an alternative embodiment, determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement, a Received Signal Strength Indicator (RSSI) of the short-range signals.

In an additional embodiment, the method further comprises controlling, by the processing arrangement, a display of an indicator over an indoor floor map interface, wherein the indicator is indicative of the determined current location of each of the one or more objects on the indoor floor map interface, and wherein the indicator moves on the indoor floor map interface as each of the one or more objects moves in real-time or near real-time in the environment.

In an additional embodiment, the method further comprises implementing, by the processing arrangement, a time-series analysis on the current location and the current state of each of the one or more objects in the environment to determine one or more time periods associated with the stationary states and the motion states for each of the one or more objects in the environment.

In an additional embodiment, the method further comprises implementing, by the processing arrangement, a statistical analysis of the information related to change in state of long-range signals and the information related to change in state of short-range signals, for filtering noise from the said information for further processing thereof.

In an additional embodiment, the method comprises determining, by the environment management system, at least one of: occupancy statistics, activity statistics and social distancing statistics for the environment, based on the current location and the current state of at least one of the one or more objects therein.

In an additional embodiment, the method further comprises controlling, by the environment management system, energy parameters of the environment, based on the current location and the current state of at least one of the one or more objects therein.

In another aspect, the present disclosure provides a system for managing an environment, the system comprising: - a long-range transceiver installed in the environment, the long-range transceiver configured to broadcast long-range signals in the environment; - a plurality of short-range transceivers installed in the environment, each of the plurality of short-range transceivers configured to broadcast short-range signals in the environment; - a processing arrangement; and - a communication interface adapted to dispose the long-range transceiver and each of the plurality of short-range transceivers in signal communication with the processing arrangement, wherein the processing arrangement is configured to: - receive from the long-range transceiver, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment; - receive from each of the plurality of short-range transceivers, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment; - determine propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state for short -range signals, respectively; - determine a current location and a current state, being either a motion state or a stationary state, of each of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals; and - communicate the current location and the current state for each of the one or more objects in the environment to an environment management system, wherein the environment management system is configured to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein.

In an additional embodiment, the long-range transceiver device comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices comprises a plurality of Bluetooth® Low Energy (BLE) sensors.

In an additional embodiment, the processing arrangement is configured to determine the propagation characteristics of the long-range signals comprises by determining a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby.

In an additional embodiment, the processing arrangement is configured to determine the propagation characteristics of the short-range signals by determining a Channel State Information (CSI) of the short-range signals by annotating channels implemented by measuring change in at least one of strength and wave characteristics of the short-range signals.

In an alternative embodiment, the processing arrangement is configured to determine the propagation characteristics of the short-range signals by determining a Received Signal Strength Indicator (RSSI) of the short-range signals.

BRIEF DESCRIPTION OF THE DRAWINGS

The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein: FIG. 1 is an illustration of a flowchart of a method for managing an environment, in accordance with an embodiment of the present disclosure; FIG. 2 is a block diagram of a system for managing an environment, in accordance with an embodiment of the present disclosure; FIGs. 3A-3C are time-series graphs depicting behaviour of Channel State Information (CSI) parameters with respect to movements of the one or more objects, in accordance with an embodiment of the present disclosure; FIG. 4 is a schematic representation of an exemplary environment depicting arrangement of long-range transceiver device and short-range transceiver devices installed therein, in accordance with an embodiment of the present disclosure; and FIG. 5 is a schematic representation of the system for managing the environment, in accordance with various embodiments of the present disclosure.

DETAILED DESCRIPTION

While the disclosed subject matter has been described in conjunction with several embodiments, it is evident that many alternatives, modifications and variations would be or are apparent to those of ordinary skill in the applicable arts. Accordingly, applicant intends to embrace all such alternatives, modifications, equivalents, and variations that are within the spirit and scope of the disclosed subject matter described herein.

The present disclosure provides a method and a system for managing an environment. The present method and system enable (allow for) monitoring occupancy and/or movement of one or more objects present in the environment. Herein, the term "environment" may refer to an indoor environment and/or an outdoor environment. In general, the environment may be a monitored zone in which the occupancy and/or movement of the one or more objects may need to be monitored. In general, the indoor environment may be a building space, such as a workspace (office), a school space, a community space or the like, whereas the outdoor environment may be an open space, such as a porch, or a terrace of the building space, or the like, without any limitations. The present disclosure has been generally described in terms of the environment being an indoor environment; however, it would be contemplated by a person skilled in the art that the teachings of the present disclosure can be applied to the outdoor environment without undue experimentation. In general, the environment may be any predefined zone without any limitations.

Further, the term "object" refers to any entity that is potentially living or non-living present in the environment. For example, the object is a person (such as, working personnel), a virtual personal assistant (such as, an autonomous program or a bot), an autonomous vehicle, such as a drone, a semi-autonomous vehicle, a manned vehicle and so forth. Notably, the object is either in a motion state or a stationary state. Herein, the object is said to be in the motion state, when a state or position of the object changes; whereas the object is said to be in the stationary state when the state or position of the object is constant with respect to time, at least for a defined period. For instance, if position of object 1 at time ti is different as compared to time t2, then the object is said to have undergone a change in state or a change in position. It may be noted that the object may potentially be in a continuous motion state, a continuous stationary state, or in the motion state for some period of time and in the stationary state for another period of time, in the environment. Herein, the determination of the motion state of the object also includes determining a speed (and further acceleration) of movement of the corresponding object. Further, the determination of the stationary state of the object also includes determining whether the object (in case of human) is sitting or standing.

In the embodiments of the present disclosure, the state of the object may be determined by tracking the wave properties such as amplitude, frequency and phase of the radio signals being broadcasted in the environment. In the present examples, the position of the objects may be represented via any geographical coordinate system, such as a horizontal coordinate system having latitude and longitude, a geodetic system such as World Geodetic System (WGS 84), North American Datum 27 (NAD27), North American Datum 83 (NAD83) and so forth.

The method and system of the present disclosure determines (or detect) the number of objects (occupants or persons) and track their activities (or movements) to provide beneficial recommendations and/or warnings based on a plurality of parameters such as, but not limited to, determined occupant density, movement history, and object proximity within the environment to ensure a safe working environment; wherein, working personnel (or objects) can potentially work at a safe distance w.r.t to one another without the risk of transmission. In any workspace (such as, office buildings), the structure is designed to accommodate a certain occupant density (such as, 1 person per 10 square meter (sqm), 2 persons per 30 sqm and so forth). Consequently, to maximize the occupant density while maintaining the safety standards to enable the working personnel to work safely in the environment, the method and system of the present disclosure perform a variety of operations such as, tracking movement of the one or more objects in and around the environment, for improving sustainability, security, safety, and reducing indoor energy consumption. Notably, the method and system of the present disclosure detects the location and activity of each of the one or more persons (or occupants) in the environment in a non-intrusive and privacy aware manner. Moreover, the method and system of the present disclosure performs such a non-intrusive and privacy aware monitoring of the one or more objects (or occupants) without requiring any type of wearable devices to be worn, or installation of any mobile application. Further, beneficially, the method and system of the present disclosure utilize the existing network infrastructure typically present in the environment and thus is cost-effective in overall implementation.

Throughout the present disclosure, the term "processing arrangement" refers to hardware, software, firmware, or a combination of these, for performing specialized data processing tasks of the method for managing an environment. The processing arrangement is a structure and/or module that includes programmable and/or non-programmable components configured to store, process and/or share information or data for managing an environment. Optionally, the processing arrangement includes any arrangement of physical or virtual computational entities capable of enhancing information to perform various computational tasks of the method. Further, it will be appreciated that the processing arrangement may be implemented as a hardware processor and/or plurality of hardware processors operating in a parallel or in a distributed architecture. Optionally, the processors in the processing arrangement are supplemented with additional computation system, such as neural networks, and hierarchical clusters of pseudo-analog variable state machines implementing artificial intelligence algorithms. In an example, the processing arrangement may include components such as a memory, a processor, a data communication interface, a network adapter and the like, to store, process and/or share information with other computing devices, such as any data source. Optionally, the processing arrangement includes, but is not limited to, a microprocessor, a micro-controller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or any other type of processing circuit, for example as aforementioned. Additionally, the processing arrangement is arranged in various architectures for responding to and processing the instructions for managing the environment. Optionally, the processing arrangement comprises a plurality of processors for parallel processing of the image data or process data. Optionally, the processing arrangement is communicably coupled to a database wirelessly and/or in a wired manner for storing the information related to managing the environment.

Optionally, the processing arrangement is communicably coupled to the database via a data communication network. It will be appreciated that the data communication network may be wired, wireless, or a combination thereof. Examples of the data communication network may include, but are not limited to, Bluetooth, infrared, Internet, a local network (such as, a TCP/IP-based network, an Ethernet-based local area network, an Ethernet-based personal area network, a Wi-Fi network, and the like), Wide Area Networks (WANs), Metropolitan Area Networks (MANs), a telecommunication network, a radio network, and Worldwide Interoperability for Microwave Access (WiMAx) networks.

Further, throughout the present disclosure, the "transceiver device" (hereinafter, sometimes, simply referred to as "transceiver") refers to an electronic device comprising suitable logic, circuitry, and interfaces that may be configured to communicate with one or more external devices, such as the processing arrangement. Examples of the transceiver may include, but is not limited to, a wi-fi access point, a router, a Bluetooth Low Energy (BLE) sensor, an antenna, a telennatics unit, a radio frequency (RE) transceiver, one or more amplifiers, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, and/or a subscriber identity module (SIM) card. Generally, the transceiver is characterized as either a long-range transceiver or a short-range transceiver based on the distance of the signals being emitted or received by the transceiver. In an example, the short-range transceiver, such as the BLE sensors have a range between 10 metres (m) to 30 m. In another example, the long-range transceiver, such as a Wi-Fi access point have a range between 40 m to 100 m. It will be appreciated that the range of the transceivers (short and long range) may be varied by increasing the power of transceiver or using a different type of transceiver without limiting the scope of the disclosure.

The method comprises receiving, by a processing arrangement, from a long-range transceiver device associated with the environment, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment. In an example, the long-range transceiver device may be installed in the environment to detect a change in state for the long-range signals broadcasted thereby due to presence of the one or more objects. In another example, the long-range transceiver device may be located outside of the environment, while being able to cover the monitored zone of the environment for the purposes of the present disclosure.

It will be appreciated that a change in state of long-range signals is directly co-related to change in state of the one or more objects in the environment, and thus the measured information related to the change in state of long-range signals can be used to estimate the change in state of the one or more objects in the environment. Generally, the long-range transceiver device is installed at central locations based on the shape and size of the environment and approximately covers an area of 1600 sqnn per long range transceiver device considering 30 objects or occupants to be monitored. In embodiments of the present disclosure, the information related to change in state of the one or more objects may be determined using measured properties associated with the long-range signals, such as amplitude, frequency, and phase. If any of the properties undergo a change, the object may be considered to have undergone a change in its state. The information related to the change in state for the long-range signals i.e., the data related to the location, state of each of the one or more objects and the data related to channel state information (CSI) is transmitted by the long-range transceiver device to the processing arrangement.

Herein, the information related to change in state of the long-range signals may include a channel state information of the long-range signals broadcasted in the environment. Specifically, the information related to the change in state of the long-range signals may be either an instantaneous channel state information (CSI) or a statistical CSI. The instantaneous CSI (or short-term CSI) means that the current channel conditions are known, which can be viewed as knowing the impulse response of a digital filter. Beneficially, said implementation provides an opportunity to adapt the transmitted signal to the impulse response and thereby optimize the received signal for spatial multiplexing or to achieve low bit error rates. Further, statistical CSI (or long-term CSI) means that a statistical characterization of the channel is known. This description can include, for example, the type of fading distribution, the average channel gain, the lineof-sight component, and the spatial correlation. As with instantaneous CSI, this information can be used for transmission optimization.

The method further comprises receiving, by the processing arrangement, from a plurality of short-range transceiver devices installed in the environment, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment. The plurality of short-range transceiver devices installed in the environment are configured to detect a change in state for short-range signals broadcasted thereby due to presence of the one or more objects. Typically, the plurality of short-range transceivers is installed in addition to the long-range transceiver device to cover smaller areas of the environment, for example, a zone having an area of 200 sqm to 300 sqm. Similar to the long-range transceivers, the plurality of short-range transceivers is configured to detect a change in state of short-range signals i.e., the plurality of short-range transceivers are configured to determine and keep track of the state and location of each of the one or more objects in the corresponding areas of the environment.

In an embodiment, the long-range transceiver device comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices comprises a plurality of Bluetooth® Low Energy (BLE) sensors. Typically, the long-range transceivers emit Wi-Fi signals and short-range transceivers emit Bluetooth® signals, which are sensitive to people's presence and activity (typically, an undesirable characteristic). For instance, the WiFi access points typically operate at both 5.8GHz and 2.4GHz and the BLE sensors operate at 2.4 GHz; wherein, both frequencies are highly sensitive to human presence (i.e., off-body shadowing impact). In general, the long-range transceiver device may be any stationary transceiver, e.g. a mobile base station located outside of the environment (e.g. in case of the environment being an outdoor space), which may be able to send and receive reflected signals from the one or more objects in the environment (i.e. monitored region/zone). The present method capitalizes on the sensitivity of the objects in the environment with respect to the emitted signals and configure the existing BLE sensors and Wi-Fi access points into a passive radar system, wherein the signals reflected from people's presence are processed for occupancy and activity monitoring in small zones. It may be appreciated that, in other examples, the long-range transceiver device may include any mobile base station nearby, or any other wireless signal transmitter using any mobile communication technology, including 6G, 5G, 4G, 3G, UWB, NB-IoT, Terahertz, etc. inside or outside of the environment, without any limitations. Further, the short-range transceiver device may be any device capable of generating short range detectable signals that is affected by human presence e.g., NFC, Magnetic field, millimetre wave, etc. without any limitations.

Generally, modern building and workspaces have a variety of transceiver devices already installed in their network infrastructure, such as WiFi access points. Further, in recent times, the BLE sensors are increasingly being included in network infrastructures of smart buildings to enable various IoT and location-based services e.g., wayfinding and proximity marketing. Beneficially, BLE sensors consume low energy, have a low-cost, and are easy to deploy when required and thus reduces the associated installation time and costs. Therefore, the present method utilizes the existing network infrastructure in office buildings and workspaces to enable the managing and/or monitoring of the environment.

The method comprises determining, by the processing arrangement, propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state of short-range signals, respectively. That is, the processing arrangement is configured to determine the propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state of short-range signals, respectively. Herein, the state of signals (including the long-range signals and the short-range signals) includes properties, such as signal strength, propagation speed, amplitude, frequency, and/or phase of the respective signals. Thereby, the propagation characteristics of radio signals i.e., both short-range and long-range signals is based on properties, such as signal strength, propagation speed, amplitude, frequency, and/or phase of the broadcasted signals. As may be understood, the properties of the path by which the radio signals will propagate governs the level and quality of the received signals. Generally, any radio signal is susceptible to obstruction, diffraction, reflection, polarization, absorption, and refraction. Further, the resultant radio signal may also be a combination of several signals interacting in the environment that may have travelled different paths, wherein the interacting signals may complement or subtract from one another, and the signals travelling via different paths may be delayed causing distortion of the resultant signal. Thus, the processing arrangement utilizes the information related to the change in state of the long-range and short-range signals to determine the propagation characteristics, which in turn may be used to track the or more objects in the environment.

In an embodiment, determining the propagation characteristics of the long-range signals comprises determining, by the processing arrangement, a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby. For this purpose, the processing arrangement implements orthogonal frequency-division multiplexing (OFDM) from each packet of the long-range signals. Herein, the CSI comprises a fine-grained physical layer (PHY) information during signal transmission and is based on the characteristics, such as the amplitude and phase of each subcarrier wave in the channel. Typically, the long-range transceiver is configured to use OFDM modulation and CSI parameters available for each subcarrier for enabling effective network optimisation and planning. The term "subcarrier" refers to a sideband of a radio frequency carrier wave (such as, the long-range signals), which is modulated to transmit additional information. Herein, the method comprises determining the channel state information of the long-range signals by employing the determined amplitude and phase of the channel and employing OFDM from each packet of the long-range signals, wherein each of the multiple closely spaced orthogonal subcarrier signals in the overlapping spectra are transmitted to carry the information in parallel to determine the channel state information of the long-range signals. The CST is measured from radio links per orthogonal frequency division multiplexing (OFDM) subcarriers for each received packet and provides a fine-grained, PHY layer information such as subcarriers and amplitude/phase information for each subcarrier. Herein, typically, the Channel state information is available from the long-range transceivers such as the WiFi network interface cards (NIC).

Beneficially, the CSI enables the method to better describe the communication link properties of the signal from the long-range transceiver to the one or more objects, which can reflect the existing reflection, diffraction, and other interference factors of the environment. The CSI represents the combined effects of the channel status, such as scattering, fading, multipath interference, shadowing, and power decay with distance. Beneficially, the method is enabled to utilize the richer signal characteristics for tracking the location of the one or more objects and obtain accurate results. Optionally, the long-range signals are modulated or de-modulated depending upon the required based on fast Fourier transformation algorithms. Notably, in contrast to RSSI signals, which provide only the amplitude information, the CSI signals provide both the subcarrier phase and amplitude information as well as better descriptions of the signal changes from the transceiver to the one or more objects than those provided by the RSSI signals.

In an embodiment, determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement, a Channel State Information (CSI) of the short-range signals by measuring change in at least one of strength and wave characteristics of the short-range signals. Herein, the term "wave characteristics" includes, but not limited to, amplitude, phase, delay and direction of the signal. Generally, the processing arrangement is configured to determine the CSI based on the signal strength and wave characteristics of the short-range signals (similar to the long-range transceivers) to enable tracking of the one or more objects in the environment. However, the frequency of transmission in the short-range signals (such as, the BLE signals) is constantly varying, thereby making it hard to measure CSI. In the present embodiments, the short-range signal packets are defined (transmitted) in a manner such that the signal packets have long sequences of bits at a first frequency, followed by long sequences of bits at a second frequency. By sending the long sequences at particular frequencies, the transmission can be converged to the said frequency for a sufficient time to measure the channel state thereat. The CSI measured at the said frequency can then be processed, by known techniques (as described above in reference to the long-range signals) to determine the propagation characteristics thereof, and thereby estimate the location (as described later in the description). Notably, CSI parameters are impacted by wireless signals from multi-path channels and the present technique may exclude signals of the direct path by cutting off signals with the shortest time of flight (ToF). The ToF of different paths may be determined using Power Delay Profile (PDP), wherein the short-range transceiver device devices may use thresholding to exclude signals when the user is not making any movement.

In another embodiment, determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement, a Received Signal Strength Indicator (RSSI) of the short-range signals. For this purpose, the plurality of short-range transceivers in the environment in communication range of each other utilizes the received signal strength (RSS) to estimate the RF signal strength at the short-range transceiver. It may be appreciated that, if the source signal strength (and/or amplitude) is known, along with the attenuation for signal strength as a function of distance, the short-range transceiver can utilize the RSS to estimate the distance of the one or more objects from the short-range transceiver to enable tracking of the one or more objects. Herein, the received signal strength (energy) can be measured for each received packet. The measured signal energy is quantized to form the received signal strength indicator (RSSI). Typically, the RSSI is used as a link quality indicator (LQI) as an indication of link quality. Generally, there are four parameters associated with RSSI: dynamic range, accuracy, linearity, and averaging period. The RSSI dynamic range is specified in decibels (dB) and indicates the minimum and maximum received signal energy that the associated transceiver is capable of measuring. For example, if the RSSI provided by a short-range transceiver has dynamic range of 92 dB (from -88 dBm to +4 dBm); the minimum signal energy the receiver can measure is -88 dBm. Also, the maximum signal energy that this receiver can report as RSSI is 4 dBm. The RSSI accuracy indicates the average error associated with each received signal strength measurement. Further, the time (i.e., the timestamp) at which the packet was received are also available to the processing arrangement. Thereby, using the RSSI and the time information, the propagation characteristics of the short-range signals can be determined. Beneficially, implementation of RSSI means that a location-estimation system can be implemented without the need for any additional hardware for the individual nodes in the network. Alternatively, a delay or phase change of the signal may be implemented for this purpose without any limitations.

In one or more embodiments, the processing arrangement is configured to annotate channels employed in the frequency hopping implementation by the plurality of short-range transceiver devices. Generally, in the environment, having the long-range and the plurality of short-range transceivers transmitting signals simultaneously, collisions and/or interferences of the transmitted signals may occur. Consequently, the overcome such a limitation, the method is configured to employ frequency hopping implementation by annotating the channels employed thereby to transmit the data on the same radio channel within overlapping time periods, without interfering with each other during operation even in presence of a radio spectrum overlap. Beneficially, the plurality of short-range transceivers such as the BLE sensors mitigate the risk of collisions via implementation of adaptive frequency hopping, wherein at each connection event, a pair of the connected short-range transceivers may use their radios to exchange packets at precisely timed intervals. Additionally, at the start of each connection event, frequency hopping occurs, with a radio channel being deterministically selected from the set of available channels using a channel selection algorithm. Each short-range transceiver in the connection will then switch to the selected channel over time and a series of connection events, communications will take place using a frequently changing series of different channels, distributed across the operating frequency band such as 2.4 GHz band, thereby significantly reducing the probability of collisions occurring.

The method comprises determining, by the processing arrangement, a current location and a current state, being either a motion state or a stationary state, of at least one of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals. Herein, the current state may either the motion state or the stationary state. That is, upon determining the propagation characteristics of the long-range signals and short-range signals, the method comprises determining the current location and a current state of the each of the one or more objects in the environment using the same. Herein, the propagation characteristics of the long-range and short-range signals are utilized by the processing arrangement to estimate the distance between the one or more objects with respect to the long-range and short-range transceivers, respectively. Such techniques, as used herein, also helps to determine the current state of the one or more objects i.e., whether the object is in a motion state, where the object is in motion as in changing location, or stationary state, where the object is stationary as in being in the same location. Generally, the steps to determine the current location and current state of at least one of the one or more objects are performed at one or more of changes in state, as determined earlier, of the at latest one of the one or more objects to effectively track the activity of the one or more objects in the environment. Herein, the at least one of the one or more objects may be objects of interest, such as humans or the like, which may be identified (separated out from other objects) based on their movements in the environment using known techniques.

Typically, the method comprises employing ranging and estimation methods such as the time of arrival (TA), time difference of arrival (TDOA), to determine the current location and the current state of the one or more objects based on the determined propagation characteristics. In an example, the processing arrangement is configured to determine (or estimate) the distance by measuring the time taken for the long-range signal to travel from the each of the one or more objects to the long-range transceiver, and the determined time taken is multiplied by the signal propagation speed to determine the distance from the object. Such methods are called time of arrival (TOA) techniques and are configured to use either radio frequency (RE) or ultrasound signals. To perform such a technique, the sender and receiver are synchronized such that the sender knows the exact time of transmission and sends the signal to the receiver. Since, generally, the exact time of transmission may be difficult to determine; optionally, the processing arrangement is configured to measure the time difference of arrival (TDOA) at two long-range transceivers, which enables the method to estimate the difference in distances between the two long-range transceivers and the one or more objects. In another example, upon determining the propagation characteristics for the short-range signals, the method comprises employing one or more machine learning algorithms to utilize the propagation characteristics of the broadcasted short-range signals via a plurality of ranging techniques to estimate the distance of a receiver to the transceiver device. For example, a pair of nodes in a sensor network having a plurality of radios in communication range of each other may use a received signal strength (RSS) technique to estimate the RF signal strength at the short-range transceiver. Further, if the source signal strength is known, along with the attenuation for signal strength as a function of distance, the short-range transceiver may use the RSS to estimate the distance of the one or more objects.

According to embodiments of the present disclosure, beneficially, the method comprises verifying the determined current location of the one or more objects using the propagation characteristics of the short-range signals by using the determined propagation characteristics of the long-range signals. It may be appreciated that since the Wi-Fi signals emitted by the long-range transceiver reaches long-distances i.e., up to 50m, the WiH signal measurements provide an overall picture and allows maintaining consistency across all zones in the environment and at the same time detecting any anomalies if present. Further, the plurality of short-range transceivers or BLE sensors are localised due to the short-range, and the short-range of BLE sensors allow for measuring channel state in small areas (virtual zones), which in return enables fine-grain monitoring of resources. It will be appreciated that some of the plurality of short-range transceivers, due to propagation and positioning of short-range and long-range transceivers, may not be within range of each other, and yet they may all associate with the same long-range transceiver. Such a verification enables the method to provide to accurate results (i.e., accurate current locations and current states of each of the one or more objects) and reduces the possibility of errors during operation; thus, resulting in a smooth and efficient operation of the method. The present techniques are based on the fact that radio signals are affected by human movement and may be tracked i.e., an estimated wireless channel having a different amplitude and phase because the movement of humans and objects changes the multipath characteristics of the channel.

In an embodiment, the method further comprises controlling, by the processing arrangement, a display of an indicator over an indoor floor map interface, wherein the indicator is indicative of the determined current location of each of the one or more objects on the indoor floor map interface, and wherein the indicator moves on the indoor floor map interface as each of the one or more objects moves in real-time or near real-time in the environment. Such indicator be used to visualize tracking of the one or more in the environment, such as a control centre of the environment. The indicator moves on the map interface as the object moves in real-time or near real time in the environment, with lag due to the time taken for travelling and processing two consequent signals. The display of the indicator over the indoor floor map interface is at the determined current location of each of the one or more objects in the environment. The indicator is represented over the indoor floor map interface having a shape such as an arrow, a solid circle, a square and the like that moves on the map interface as the object moves in real-time or near real-time in the environment. The indoor floor map interface refers to a structured set of user interface elements rendered on a display screen of the indicator. Optionally, the indoor floor map interface is configured to interact with a user to display the current location of the one or more objects, and to allow the user to adjust the screen size of the indoor floor map interface, to enable a clear view of the nearby location of the object on the indoor floor map interface. In some examples, the indoor floor map interface displays a three-dimensional view of surroundings of the current location of the one or more objects, such that the indicator moves over the three-dimensional view on the indoor floor map interface to indicate the current location of each object.

In an embodiment, the method further comprises implementing, by the processing arrangement, a time-series analysis on the current location and the current state of each of the one or more objects in the environment to determine one or more time periods associated with the stationary states and the motion states for each of the one or more objects in the environment. That is, using one or more time-series analysis algorithms such as an internet gateway time series, the processing arrangement can determine for how long a given object may be stationary, or may be moving, in the environment. Thereby, the present method is able to determine and track the physical activity (or current state) and current location of the one or more objects in the environment. The processing arrangement may utilize the time periods associated with each state of the one or more objects in the environment to generate energy and safety recommendations to the environment for efficient and effective management and power conservation, as discussed later in more detail.

In an embodiment, the method further comprises implementing, by the processing arrangement, a statistical analysis of the information related to change in state of long-range signals and the information related to change in state of short-range signals, for filtering noise from the said information for further processing thereof. Herein, the term "statistical analysis" has been broadly used to encompass machine learning and deep learning techniques for the purposes of information analysis as per embodiments of the present disclosure. Generally, the data sets related to the change in states for the long-range and short-range signals comprises large amounts of noise. Thus, to filter the unwanted noise from the said information, the method comprises performing the statistical analysis of the information using one or more techniques to enhance data analysis in the presence of high noise levels. For example, traditional outlier detection techniques such as distance-based, clustering-based, and Local Outlier Factor (LOF) based analysis of the information related to change in state for the long-range and short-range signals, may be employed. Further, typically, various machine learning (ML) and statistical analysis (SA) techniques may be used to associate the activity and occupancy level with variations of the received signal in the virtual zone. To perform such a technique, the method comprises generating a dataset for training the ML algorithm based on signal characteristics (such as the channel state information, the RSSI etc.) at different occupancy levels and activities of the occupants in the environment. Notably, the ML algorithm or the SA technique being employed may be specific to the environment, the type of transmitters being deployed, and the frequency of wireless signals being broadcasted in the environment. Alternatively stated, the ML algorithm or the SA technique may be defined for a specific number of transceivers, the ML/SA may be defined for a specific arrangement or placement of transmitters in the environment, or the ML/SA may be generic i.e., configured for all possible configurations of the aforementioned parameters to increase the versatility of the system. Further, the method comprises training a machine learning algorithm, such as a dense neural network, long short term memory (LSTM) network, convolutional neural network (CNN) and the like or various statistical analysis (SA) techniques on the generated data set to capture the temporal and spatial impacts of occupancy and activity on different types of signals.

Typically, the environment is divided into virtual zones (size of the virtual zones may vary depending on the implementation) to effectively manage the environment by generating a dataset of the received wireless signals to capture the impact of at least one of the following parameters: different occupancy levels, different activities, different number of transceivers, different types of transceivers, different placement of sensors, different sizes of the virtual zones or the environment. Herein, upon generating the dataset of the received wireless signals, the received signals are preprocessed to remove noise and unrelated data to improve the accuracy and efficiency of the method and reduce the size of the dataset.

Optionally, based on the implementation and available resources, the method comprises training a separate model for each virtual zone in the environment. The machine learning model is trained for each specific zone/ zone type, for each specific environment type, for each specific transceiver placement and/or corresponding arrangement, for a specified number of occupants activities (for example, 20 occupants for each ML model), for each specific transceiver types and/or frequency ranges, and various possible combinations of transmitters or receivers and their types. Optionally, the ML algorithm or the SA technique may be retrained to capture the environmental impacts of the environment and track the greenhouse gas (GHG) emissions to beneficially reduce the said GHG emissions and make the system more sustainable and eco-friendlier. Optionally, the present method includes automatically collecting data and re-training the machine learning model, making it resilient to environmental changes, such that the accuracy of the machine learning model is unaffected by environmental changes in environment.

The method further comprises communicating, by the processing arrangement, the current location and the current state for each of the one or more objects in the environment to an environment management system, wherein the environment management system is configured to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein. That is, upon determining the current location and current state of at least one of the one or more objects, the processing arrangement is configured to communicate the current location and the current state of at least one of the one or more objects in the environment to the environment management system (EMS). In an example, the processing arrangement may communicate the current location and the current state for each of the one or more objects in the environment to the environment management system via an application programming interface (API). Herein, the term "application programming interface" or API refers to a software interface of the EMS to communicate information related to the current state and current location of each of the one or more objects to and from the processing arrangement. Interfacing between individual smart building applications. Examples of API include, but are not limited to, a graphical user interface (GUI), Command line interface (CLI), Natural Language Interface (NLI), Menu based Interface (MBI). It may be appreciated that other means for establishing communication between the processing unit and the EMS may be implemented without departing from the scope and the spirit of the present disclosure.

Herein, the term "environment management system" refers to a structure and/or module that includes programmable and/or non-programmable components configured to store, process and/or share information or data and control the operations parameters for managing the environment. Optionally, the EMS includes any arrangement of physical or virtual computational entities capable of enhancing information to perform various computational tasks. Furthermore, it will be appreciated that the EMS may be implemented as a hardware processor and/or plurality of hardware processors operating in a parallel or in a distributed architecture. Optionally, the EMS is supplemented with additional computation system, such as neural networks, and hierarchical clusters of pseudo-analog variable state machines implementing artificial intelligence algorithms. Optionally, the EMS may include components such as a memory, a processor, a data communication interface, a network adapter and the like, to store, process and/or share information with other computing devices, such as the processing arrangement and the electrical systems and appliances in the environment.

In an embodiment, the method comprises controlling, by the environment management system, energy parameters of the environment, based on the current location and the current state of at least one of the one or more objects therein. Beneficially, to conserve power during operation of the environment (such as, during working hours of a workspace), the energy parameters of the environment and the electrical systems and appliances therein such as, the power input, amplitude, current, voltage and so forth are controlled by the EMS. Herein, the EMS is configured to adapt the operations parameters of the environment based on the communicated information. The EMS may comprise functionalities such as, access control, video surveillance, fire alarms, HVAC control, programmable lighting, electric power management, etc. The term "operations parameters" refers to various parameters that are controlled by the EMS; to effectively manage the environment, including a plurality of connected electrical systems appliances therein; for example, by turning off the power supply to the electrical systems, reducing the power input, switching to a power conservation mode and so forth. The EMS is configured to monitor, supervise the one or more objects in the environment and adapts the operations parameters to manage the environment efficiently and effectively. Such adaption by the EMS by changing operations parameters of the environment may be contemplated by a person skilled in the art, as is common in smart buildings, and thus has not been described further for the brevity of the present disclosure.

The method further comprises providing an indication of safety level, evacuation guidance, etc., for instance, based on number of humans in the environment and various distances between the same, the process for which may be contemplated by a person skilled in the art and thus has not been described herein for the brevity of the present disclosure. That is, the EMS is further configured to provide information on the indoor management functions including, but not limited to, current status, archived historical information, summaries, analysis, displays, and reports on control and management functions of the environment. Optionally, the EMS controls functions such as announcements, alarms, warnings, alerts and so forth to enable diagnostic monitoring and reporting of the one or more objects, system functions, nodes, devices, and communication networks. Generally, radio frequency (RF) based device-free sensing has the advantage of being non-intrusive. The EMS takes advantage of existing BLE sensors and WiFi access points that are readily available in smart buildings to offer a fine grain un-intrusive localisation tracking system that does not require any mobile app or wearable device. Herein, the EMS using a grid of BLE sensors, WiFi access points and a WiFi and BLE enabled internet gateway, as the WiFi and BLE signals are very sensitive to people's movement; and beneficially enables the system or method to capture the presence and activities of the one or more objects in the environment, wherein the WiFi and BLE signals may travel through the walls such that the one or more objects are not required to be in the line-of-sight (LOS).

In an exemplary scenario of an environment comprising of four zones, wherein each of the four zones (namely, Z1, Z2, Z3, Z4) are enabled with electrical systems and appliances such as, but not limited to, lighting arrangements (such as smart LEDS, smart displays, electric bulbs and so forth), temperature management systems (such as, air conditioners, heaters), ducts and ventilation systems and so forth. If the EMS determines that zone 1Z2' does not have an occupant present based on the communicated current location and current states of each of the one or more objects; the EMS is configured to power off or reduce the output of the working electrical systems and appliances in the said zone '72' (of the environment) to conserve power and associated costs during operation.

In another embodiment, the method further comprises determining, by the environment management system, at least one of: occupancy statistics, activity statistics and social distancing statistics for the environment, based on the current location and the current state of at least one of the one or more objects therein. To enable the EMS to provide beneficial recommendations and warnings related to the environment, the EMS is further configured to determine the occupancy statistics, activity statistics and the social distancing statistics of the one or more objects i.e., the current location of the one or more objects is tracked to generate the history of activities and movements of the one or more objects. The occupancy statistics, activity statistics and social distancing statistics refers to the information related to the activity and movements of the one or more objects in the environment. For example, the occupancy statistics and activity statistics of individual or groups may be determined based on history of location of the one or more objects in the environment. Further, the social distancing statistics refers to the information related to the distance between each of the one or more objects. Herein, the social distancing statistics are configured to enable the method to effectively maintain a safe distance between each of the one or more objects and significantly reduce the risk of transmission in the environment.

In a practical innplennentational scenario, to detect the number of occupants and activity in a virtual zone (such as, a room of size 5m x 5m), the system comprises at least one transmitter (such as the long-range transceiver and/or the plurality of short-range transceivers) and at least one receiver in the vicinity of the zone. Herein, the at least one receiver is configured to capture the broadcasted signals from the at least one wireless transmitter existing in proximity of the virtual zone. Upon receiving the broadcasted signals, the received signals are passed to the cloud service via an internet gateway or analysed locally. Typically, the broadcasted signals are analysed locally by the processing arrangement or transmitted to a remote server through the communication interface for further analysis. It will be appreciated that although the system and/or method for managing the environment is operational with a single transmitter and receiver; in practical scenarios, the system may comprise multiple transceivers based on the requirement to cover the entire environment with a higher accuracy. Generally, if the number of existing wireless transmitters in the environment are not adequate, extra transmitters are needed to be deployed; wherein the placement of the installed transmitters are important and specific configurations of transmitters placements is considered for different environments to achieve the best accuracy based on the implementation. Beneficially, the deployed transmitters may be used for other applications simultaneously for example, communication, navigation, proximity marketing. Further, signal processing is performed on the signal by the processing arrangement (if done locally) to capture the channel state information of the broadcasted signals. Notably, the signal processing is done either on the internet gateway or cloud, or the processing arrangement. Furthermore, upon performing the signal processing, statistical analysis of the data for filtering and noise removal based on both temporal and special features of the received signals is implemented.

The present disclosure also relates to the system as described above. Various embodiments and variants disclosed above apply mutatis mutandis to the system.

In another aspect, the present disclosure also provides a system for managing an environment. The system comprises a long-range transceiver installed in the environment, wherein the long-range transceiver is configured to broadcast long-range signals in the environment. Further, the system comprises a plurality of short-range transceivers installed in the environment, wherein each of the plurality of short-range transceivers configured to broadcast short-range signals in the environment. Furthermore, the system comprises a processing arrangement and a communication interface adapted to dispose the long-range transceiver and each of the plurality of short-range transceivers in signal communication with the processing arrangement. Herein, the processing arrangement is configured to receive from the long-range transceiver device, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment. Further, the processing arrangement is configured to receive from each of the plurality of short-range transceiver devices, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment. Furthermore, the processing arrangement is configured to determine propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state of short-range signals, respectively. Furthermore, the processing arrangement is configured to determine a current location and a current state, being either a motion state or a stationary state, of each of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals and communicate the current location and the current state for each of the one or more objects in the environment to an environment management system, wherein the environment management system is configured to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein.

In an additional embodiment, the long-range transceiver device comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices comprises a plurality of Bluetooth® Low Energy (BLE) sensors.

In an additional embodiment, the processing arrangement is configured to determine the propagation characteristics of the long-range signals comprises by determining a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby.

In an additional embodiment, the processing arrangement is configured to determine the propagation characteristics of the short-range signals by determining a Channel State Information (CSI) of the short-range signals by measuring change in at least one of strength and wave characteristics of the short-range signals.

In an alternative embodiment, the processing arrangement is configured to determine the propagation characteristics of the short-range signals by determining a Received Signal Strength Indicator (RSSI) of the short-range signals.

Notably, the method and system of the present disclosure employ static BLE and Wi-Fl enabled devices that are readily available in smart buildings to offer a fine grain and un-intrusive localisation tracking system that does not require any mobile application or wearable device. Further, based on the processed and monitored activity in the environment, feedbacks and/or reports are generated to further recommendations and/or warnings to the environment management system. The provided recommendations and/or warnings have significant long-term benefits to building operations and nationwide infrastructure by substantial savings in energy and carbon footprints by allowing the building services such as heating, air conditioning, lighting, etc. to be tailored to occupants' needs. Moreover beneficially, building regulations are moving towards a point wherein optimizing operational energy will become a requirement and thus having such technology enable the calibration and optimisation of energy and/or occupants in the buildings in use potentially improves the design measures. Thus, the present method and system provides privacy-aware, low-cost, and accurate monitoring in zones as small as 4 square meters (sqm) and various activity levels of the objects (or occupants).

DETAILED DESCRIPTION OF THE DRAWINGS

Referring to FIG. 1, illustrated is a flowchart of a method 100 for managing an environment, in accordance with an embodiment of the present disclosure. As shown, the method 100 comprises steps 102, 104, 106, 108, 110, and 112.

At step 102, the method 100 comprises receiving, by a processing arrangement, from a long-range transceiver device associated with the environment, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment. That is, the information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects in the environment is received by the processing arrangement from the long-range transceiver device.

At step 104, the method 100 comprises receiving, by the processing arrangement, from a plurality of short-range transceiver devices installed in the environment, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment. That is, the information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects in the environment is received by the processing arrangement from the plurality of short-range transceiver devices.

At step 106, the method 100 comprises determining, by the processing arrangement, propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state of short-range signals, respectively. That is, upon receiving the information related to the change in state from the long-range transceiver device and the plurality of short-range transceiver devices, the propagation characteristics of the long-range signals and the short-range signals are determined by the processing arrangement based on the information related to change in state of long-range signals and short-range signals, respectively.

At step 108, the method 100 comprises determining, by the processing arrangement, a current location and a current state of at least one of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals, the current state being either a motion state or a stationary state. That is, upon determining the propagation characteristics of the long-range and short-range signals, the current location and the current state of at least one of the one or more objects is determined by the processing arrangement to enable tracking of each of the one or more objects in the environment.

At step 110, the method 100 comprises communicating, by the processing arrangement, the current location and the current state for each of the one or more objects in the environment to an environment management system. That is, upon determining the current location and the current state of at least one of the one or more objects, the processing arrangement is configured to transmit the current locations and states to the environment management system via the application programming interface to enable the environment management system to manage the environment.

And, at step 112, the method 100 comprises configuring the environment management system to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein. That is, the EMS is configured to adapt the operation parameters of the environment based on the received information from the processing arrangement, to manage the environment efficiently and effectively. For example, the operations parameters may be the energy parameters (such as power input, voltage/current input etc.) for the electrical appliances in the environment, wherein based on detection of vacancy of the environment (or a zone in the environment), the energy parameters may be varied by the environment management system to save power and reduce the associated operational costs.

Referring to FIG. 2, illustrated is a block diagram of a system 200 for managing an environment 202, in accordance with an embodiment of the present disclosure. As shown, the system 200 comprises a long-range transceiver device 204 associated with the environment 202, wherein the long-range transceiver device 204 is configured to broadcast long-range signals in the environment 202. The system 200 further comprises a plurality of short-range transceiver devices 206 installed in the environment 202, wherein each of the plurality of short-range transceiver devices 206 is configured to broadcast short-range signals in the environment 202. The system 200 further comprises a processing arrangement 208, and a communication interface 210 adapted to dispose the long-range transceiver device 204 and each of the plurality of short-range transceiver devices 206 in signal communication with the processing arrangement 208. Herein, the processing arrangement 208 is configured to receive from the long-range transceiver device 204, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects 212 in the environment 202 via the communication interface 210. Further, the processing arrangement 208 is configured to receive from each of the plurality of short-range transceiver devices 206, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects 212 in the environment 202 via the communication interface 210. The processing arrangement 208 is configured to determine propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state of short-range signals, respectively. Furthermore, the processing arrangement 208 is configured to determine a current location and a current state, being either a motion state or a stationary state, of each of the one or more objects 212 in the environment 202 based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals. Furthermore, the processing arrangement 208 is configured to communicate the current location and the current state for each of the one or more objects 212 in the environment 202 to an environment management system 214 (such as, via an application programming interface (API) 216), wherein the environment management system 214 is configured to adapt operations parameters of the environment 202 based on the current location and the current state of at least one of the one or more objects therein.

Referring to FIGs. 3A-3C, illustrated are time-series graphs 300A-300C depicting behaviour of Channel State Information (CSI) parameters with respect to movements of the one or more objects, in accordance with an embodiment of the present disclosure. Herein, the CSI parameter represents CSI amplitude of the signals (long-range and short-range signals) broadcasted thereby due to the presence and movement of the one or more objects. Further, the one or more objects may be considered as the occupants or persons in the environment and thus, the time series graphs illustrate the behaviour of the one or more objects in various states, such as a stationary state, a motion state or a rapid-motion state. Referring to FIG. 3A, illustrated is a time-series graph 300A depicting behaviour of CSI Amplitude of the signal broadcasted due to the movement i.e., a motion state of an object. For example, the motion state may be walking in the environment. Referring to FIG. 3B, illustrated is a time-series graph 300B depicting behaviour of CSI Amplitude of the signal broadcasted in a stationary state of the object. For example, the stationary state may be sitting or standing in the environment. Referring to FIG. 3C, illustrated is a time-series graph 300C depicting behaviour of CSI Amplitude of the signal broadcasted due to the movement i.e., a rapid-motion state of an object. For example, the rapid-motion state may be running in the environment. Such reference time-series graphs 300A-300C can be utilized to compare the determine CSI characteristics, to determine a current state of a given object.

Referring to FIG. 4, illustrated is a schematic representation of an exemplary environment 400, in accordance with an embodiment of the present disclosure. As shown, the environment 400 has been divided into a plurality of virtual zones 402A-4021, wherein the plurality of virtual zones 402A-4021 are not physical boundaries (i.e., walls) but even or uneven space distributions to effectively manage the environment 400. For example, the dimensions of the environment 202 may be 6 metres x 6 meters x 2 meters and wherein dimensions of each of the nine virtual zones is 2 metres x 2 meters x 2 meters. Further, the environment 400 comprises a long-range transceiver device 404 and a plurality of short-range transceiver devices 406 to track the current location and current state of each of one or more objects 412 in each of the plurality of virtual zones 402A-4021 of the environment 400 based on the propagation characteristics of the broadcasted signals thereby. Herein, the long-range transceiver device 404 and the plurality of short-range transceiver devices 406 are configured to transmit information related to change in state of long-range signals and short-range signals, respectively, broadcasted thereby due to presence of one or more objects 412 in the environment 400 to a processing arrangement (not shown) via a communication interface 410 for determining the propagation characteristics of the long-range signals and the short-range signals. Generally, the short-range transceiver devices 406 are disposed 5-10 meters apart from each other (or can be based on their existing configuration if already existed in the environment) which allows for covering a large area with a small number of sensors.

Referring to FIG. 5, illustrated is a schematic representation of an integrated system 500, in accordance with various embodiments of the present disclosure. As shown, the system 500 is implemented for an environment 502. The system 500 comprises a long-range transceiver device 504 and a plurality of short-range transceiver devices 506. The system 500 also comprises a processing arrangement 508 implemented as a component of a cloud-based platform, wherein using a communication interface 510, time series of signal strength or amplitude associated with broadcasted signals due to the presence of one or more objects 512 are transmitted to the processing arrangement 508. Further, as shown, the processing arrangement 508 is configured to extract CSI parameters from the information provided by the long-range transceiver device 504 and the plurality of short-range transceiver devices 506. The information enables to capture the physical activity (current state) and location of the one or more objects 512 in the environment 502 using machine learning algorithms, wherein the output is used by an Environment management system 514 to generate energy and safety recommendations for the environment. As shown, the processing arrangement 208 is communicatively coupled to an Environment management system (EMS) 514 of a building 516 whose environment 502 is required to be managed. The EMS 514 is configured to control and monitor the mechanical and electrical equipment such as heating, cooling, ventilation, lighting, power, fire, lifts, and security systems of the building 516. Beneficially, integrating the present system 500 with the EMS 514 enables controlling operational parameters of various components of building 516 to occupants' needs based on real-time occupancy and usage. As shown, the system 500 also comprises an analytics dashboard 518 configured to perform one or more statistical or time-series analysis on the determined information to derive beneficial inferences and results therefrom.

Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural.

Claims (15)

1. CLAIMS1. A method (100) for managing an environment (202, 400), the method (100) comprising: - receiving, by a processing arrangement (208), from a long-range transceiver device (204) associated with the environment (202), information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects (212) in the environment (202,400); - receiving, by the processing arrangement (208), from a plurality of short-range transceiver devices (206) installed in the environment, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects (212) in the environment; - determining, by the processing arrangement, propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state for short -range signals, respectively; - determining, by the processing arrangement, a current location and a current state of at least one of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals, the current state being either a motion state or a stationary state; - communicating, by the processing arrangement, the current location and the current state for each of the one or more objects in the environment to an environment management system (214); and - configuring the environment management system (214) to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein.
2. 2. A method (100) according to claim 1, wherein the long-range transceiver device (204) comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices (206) comprises a plurality of Bluetooth® Low Energy (BLE) sensors.
3. 3. A method (100) according to any one of claims 1 or 2, wherein determining the propagation characteristics of the long-range signals comprises determining, by the processing arrangement (208), a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby.
4. 4. A method (100) according to any one of claims 1, 2 or 3, wherein determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement (208), a Channel State Information (CSI) of the short-range signals by measuring change in at least one of strength and wave characteristics of the short-range signals.
5. 5. A method (100) according to any one of claims 1, 2 or 3, wherein determining the propagation characteristics of the short-range signals comprises determining, by the processing arrangement (208), a Received Signal Strength Indicator (RSSI) of the short-range signals.
6. 6. A method (100) according to any one of the preceding claims further comprising controlling, by the processing arrangement (208), a display of an indicator over an indoor floor map interface, wherein the indicator is indicative of the determined current location of each of the one or more objects on the indoor floor map interface, and wherein the indicator moves on the indoor floor map interface as each of the one or more objects moves in real-time or near real-time in the environment (202).
7. 7. A method (100) according to any one of the preceding claims further comprising implementing, by the processing arrangement (208), a time-series analysis on the current location and the current state of each of the one or more objects in the environment (202, 400) to determine one or more time periods associated with the stationary states and the motion states for each of the one or more objects (212) in the environment (202, 400).
8. 8. A method (100) according to any one of the preceding claims further comprising implementing, by the processing arrangement (208), a statistical analysis of the information related to change in state of long-range signals and the information related to change in state of short-range signals, for filtering noise from the said information for further processing thereof.
9. 9. A method (100) according to any one of the preceding claims further comprising determining, by the environment management system (214), at least one of: occupancy statistics, activity statistics and social distancing statistics for the environment, based on the current location and the current state of at least one of the one or more objects (212) therein.
10. 10. A method (100) according to any one of the preceding claims further comprising controlling, by the environment management system (214), energy parameters of the environment (202, 400), based on the current location and the current state of at least one of the one or more objects (212) therein.
11. 11. A system (200, 500) for managing an environment (202, 400), the system (200, 500) comprising: - a long-range transceiver (204) associated with the environment (202, 400), the long-range transceiver (204) configured to broadcast long-range signals in the environment; - a plurality of short-range transceivers (206) installed in the environment, each of the plurality of short-range transceivers (206) configured to broadcast short-range signals in the environment; - a processing arrangement (208); and - a communication interface (210) adapted to dispose the long-range transceiver and each of the plurality of short-range transceivers in signal communication with the processing arrangement (208), wherein the processing arrangement is configured to: - receive from the long-range transceiver, information related to change in state of long-range signals broadcasted thereby due to presence of one or more objects (212) in the environment; - receive from each of the plurality of short-range transceivers, information related to change in state of short-range signals broadcasted thereby due to presence of one or more objects (212) in the environment; - determine propagation characteristics of the long-range signals and the short-range signals based on the information related to change in state of long-range signals and the information related to change in state for short -range signals, respectively; - determine a current location and a current state, being either a motion state or a stationary state, of each of the one or more objects in the environment based on the propagation characteristics of the short-range signals and verified by the propagation characteristics of the long-range signals; and - communicate the current location and the current state for each of the one or more objects in the environment to an environment management system (214), wherein the environment management system (214) is configured to adapt operations parameters of the environment based on the current location and the current state of at least one of the one or more objects therein.
12. 12. A system (200, 500) according to claim 11, wherein the long-range transceiver device (204) comprises at least one WiFi access point, and wherein the plurality of short-range transceiver devices (206) comprises a plurality of Bluetooth® Low Energy (BLE) sensors.
13. 13. A system (200, 500) according to any one of claims 11 or 12, wherein the processing arrangement (208) is configured to determine the propagation characteristics of the long-range signals comprises by determining a Channel State Information (CSI) of the long-range signals by measuring change in at least one of amplitude and phase of a channel employed thereby.
14. 14. A system (200, 500) according to any one of claims 11, 12 or 13, wherein the processing arrangement (208) is configured to determine the propagation characteristics of the short-range signals by determining a Channel State Information (CSI) of the short-range signals by measuring change in at least one of strength and wave characteristics of the short-range signals.
15. 15. A system (200, 500) according to any one of claims 11, 12 or 13, wherein the processing arrangement (208) is configured to determine the propagation characteristics of the short-range signals by determining a Received Signal Strength Indicator (RSSI) of the short-range signals.