A Low-Resolution IR-Array as a Doorway Occupancy Counter in a Smart Building

Abstract

A doorway counter, which detects a person underpass at a room entry/exit, may be the most accurate type of occupancy counters used in buildings. An occupancy counter, which uses a low-resolution IR-imager and Raspberry Pi board has been constructed. The imager provides only 8 x 8 pixels initial resolution, but it has been enhanced using two-dimensional interpolation. Due to the low absolute accuracy in temperature measurements, the imager is set to measure temperature difference between a target and background. Signal-to-noise ratio is also increased using discrete two-dimensional convolution filtering. The blob detection and tracking algorithm deduces the direction of an occupant and finally increments or decrements the counter. A heat signature varies between people and depends on person’s clothing. An on-board server on Raspberry Pi distributes the data via Wi-Fi to any client device in the net. The complete system includes also wireless PIR-sensors. The low-resolution IR occupancy counter has been compared with counters based on different technologies. The benefits of a low-resolution IR-imager are privacy preservation, operation capability in total darkness, energy-efficient passive operation and a low price.

Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways

“…The designed adaptive threshold technique to preserve human targets and remove background by the authors functions well for indoor multiple human targets. Within a smart building set-up, Maaspuro, in [21], studied an application of IR sensor array as a doorway occupancy counter using Kalman filter tracking algorithm and reported an accuracy between 89-92%. Doherty et al,in [22], implemented a novel indoor localization system by combining sensor technology and machine learning methods (logistic regression, K-Nearest neighbours, support vector machine, and a feedforward neural network) to collect and analyze human occupancy data in an indoor toilet.…”