Estimating Indoor Occupancy Through Low-Cost BLE Devices

Demrozi, Florenc; Turetta, Cristian; Chiarani, Fabio; Kindt, Philipp H.; Pravadelli, Graziano

doi:10.1109/jsen.2021.3080632

Cited by 30 publications

(11 citation statements)

References 27 publications

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“…The BLE [ 29 ] device uses several modes to communicate with other devices or the outside world (even via the internet). These mechanisms follow the Generic Access Profile (GAP) guidelines.…”

Section: Methodsmentioning

confidence: 99%

Health, Security and Fire Safety Process Optimisation Using Intelligence at the Edge

D’Souza

Mukhopadhyay

Sheng

2022

Sensors

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The proliferation of sensors to capture parametric measures or event data over a myriad of networking topologies is growing exponentially to improve our daily lives. Large amounts of data must be shared on constrained network infrastructure, increasing delays and loss of valuable real-time information. Our research presents a solution for the health, security, safety, and fire domains to obtain temporally synchronous, credible and high-resolution data from sensors to maintain the temporal hierarchy of reported events. We developed a multisensor fusion framework with energy conservation via domain-specific “wake up” triggers that turn on low-power model-driven microcontrollers using machine learning (TinyML) models. We investigated optimisation techniques using anomaly detection modes to deliver real-time insights in demanding life-saving situations. Using energy-efficient methods to analyse sensor data at the point of creation, we facilitated a pathway to provide sensor customisation at the “edge”, where and when it is most needed. We present the application and generalised results in a real-life health care scenario and explain its application and benefits in other named researched domains.

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Section: Methodsmentioning

confidence: 99%

Health, Security and Fire Safety Process Optimisation Using Intelligence at the Edge

D’Souza

Mukhopadhyay

Sheng

2022

Sensors

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“…Hence, H = [ℎ 1 , ℎ 2 , ..., ℎ 𝑁 ] for a received WiFi Frame is a vector of complex values ℎ 𝑖 , where the index 𝑖 identifies the subcarrier. The magnitude of every complex number ℎ 𝑖 represents the attenuation the signal has undergone, whereas the phase expresses the phase change induced, e.g., by human motion [3]. Using Automatic Gain Control (AGC), every WiFi receiver continuously adjusts the CSI magnitude on average over all subcarriers to lie within a certain range.…”

Section: A Background: Channel State Information (Csi)mentioning

confidence: 99%

“…In contrast, carrying out all processing steps in real-time, adjusting all parameter values Furthermore, since no tool to deliver preprocessed data to a classification model in real-time is available, the vast majority of works, e.g. [3], [11], [12], [13], elude the effort in creating such an online workflow. They instead subdivide previously recorded CSI data into testing and training data.…”

Section: Shortcomingsmentioning

confidence: 99%

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WiFiEye -- Seeing over WiFi Made Accessible

Kindt¹,

Turetta²,

Demrozi³

et al. 2022

Preprint

Self Cite

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While commonly used for communication purposes, an increasing number of recent studies consider WiFi for sensing. In particular, wireless signals are altered (e.g., reflected and attenuated) by the human body and objects in the environment. This can be perceived by an observer to infer information on human activities or changes in the environment and, hence, to "see" over WiFi. Until now, works on WiFi-based sensing have resulted in a set of custom software tools -each designed for a specific purpose. Moreover, given how scattered the literature is, it is difficult to even identify all steps/functions necessary to build a basic system for WiFi-based sensing. This has led to a high entry barrier, hindering further research in this area. There has been no effort to integrate these tools or to build a general software framework that can serve as the basis for further research, e.g., on using machine learning to interpret the altered WiFi signals. To address this issue, in this paper, we propose WiFiEye -a generic software framework that makes all necessary steps/functions available "out of the box". This way, WiFiEye allows researchers to easily bootstrap new WiFi-based sensing applications, thereby, focusing on research rather than on implementation aspects. To illustrate WiFiEye's workflow, we present a case study on WiFi-based human activity recognition.

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“…et al [31] sent them the packets periodically, and presented a method for estimating the geographic location of visitors inside a museum. Demrozi et al [32] introduced a method for estimating the number of people in a specific area by bringing a BLE-based pattern recognition model into the world that can detect cognitive changes of people based on BLE that is similar to previous Wi-Fi-based systems while reducing cost and installation effort, and raising practicality.…”

Section: Related Workmentioning

confidence: 99%

Multilink Internet-of-Things Sensor Communication Based on Bluetooth Low Energy Considering Scalability

2021

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As the growth rate of the internet-of-things (IoT) sensor market is expected to exceed 30%, a technology that can easily collect and processing a large number of various types of sensor data is gradually required. However, conventional multilink IoT sensor communication based on Bluetooth low energy (BLE) enables only the processing of up to 19 peripheral nodes per central device. This study suggested an alternative to increasing the number of IoT sensor nodes while minimizing the addition of a central processor by expanding the number of peripheral nodes that can be processed per central device through a new group-switching algorithm based on Bluetooth low energy (BLE). Furthermore, this involves verifying the relevancy of application to the industry field. This device environment lowered the possibility of data errors and equipment troubles due to communication interference between central processors, which is a critical advantage when applying it to industry. The scalability and various benefits of a group-switching algorithm are expected to help accelerate various services via the application of BLE 5 wireless communication by innovatively improving the constraint of accessing up to 19 nodes per central device in the conventional multilink IoT sensor communication.

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Estimating Indoor Occupancy Through Low-Cost BLE Devices

Cited by 30 publications

References 27 publications

Health, Security and Fire Safety Process Optimisation Using Intelligence at the Edge

Health, Security and Fire Safety Process Optimisation Using Intelligence at the Edge

WiFiEye -- Seeing over WiFi Made Accessible

Multilink Internet-of-Things Sensor Communication Based on Bluetooth Low Energy Considering Scalability

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