Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm

Abstract

Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

Novel smart home system architecture facilitated with distributed and embedded flexible edge analytics in demand‐side management

“…Finally, the elderly population is rapidly increasing worldwide and has been forecasted to reach a staggering 2 billion . Helping the elderly to live conveniently and safely has become an important social issue . Researchers who address this issue have developed various techniques to localize residents in indoor environments.…”

“…Researchers who address this issue have developed various techniques to localize residents in indoor environments. In the future, wearable inertial sensing combined with passive infrared informatics will be developed and ported easily onto the proposed flexible HES device prototype for smart home applications, such as home automation and home health care/safety. Moreover, statistical analysis of Wi‐Fi received signal strength fingerprints will be realized for the detection of occupants' location and estimation of their velocity in indoor environments.…”

“…In the future, wearable inertial sensing combined with passive infrared informatics will be developed and ported easily onto the proposed flexible HES device prototype for smart home applications, such as home automation and home health care/safety. Moreover, statistical analysis of Wi‐Fi received signal strength fingerprints will be realized for the detection of occupants' location and estimation of their velocity in indoor environments. Shi et al present a novel building heating, ventilation, and air conditioning (HVAC) control algorithm in terms of an occupancy‐based model predictive control framework with occupancy predictions to improve the energy efficiency of HVAC, as electrical energy is wasted through inefficient operation of HVAC due to the lack of reliable building occupancy measurements and predictions.…”

“…In Shi et al, a penalty factor is introduced and used to allow occupants to determine the optimal trade‐off between comfort and energy efficiency. Wi‐Fi received signal strength fingerprints will be helpful to improve indoor positioning precision, relating precise/detailed occupancy predictions with occupants' behavior (location and presence).…”

Design and Implementation of Directional Sensors for Privacy-Ensured Device-Free Target Localization in Indoor Environment

“…Another way to localize a device-free target is to use infrared sensors [23]. e wavelength of infrared light ranges from 750 nm to 1 mm.…”