Abstract

Direction-sensitive visitor counting sensors can be used in demand-controlled ventilation (DCV). The counting performance of two light beam sensors and three camera sensors, all direction sensitive, was simultaneously evaluated at an indoor location. Direction insensitive sensors (two mat sensors and one light beam sensor) were additionally tested as a reference. Bidirectional counting data of free people flow was collected for 36 days in one-hour resolution, including five hours of manual counting. Compared to the manual results, one of the light beam sensors had the most equally balanced directional overall counting errors (4.6% and 5.2%). The collected data of this sensor was used to model the air transportation energy consumption of visitor counting sensor-based DCV and constant air volume ventilation (CAV). The results suggest that potential savings in air transportation energy consumption could be gained with the modeled DCV as its total daily airflow during the test period was 54% of the total daily airflow of the modeled CAV on average. A virtually real-time control of ventilation could be realized with minute-level counting resolution. Site-specific calibration of the visitor counting sensors is advisable and they could be complemented with presence detectors to avoid unnecessary ventilation during unoccupied periods of the room. A combination of CO2 and visitor counting sensors could be exploited in DCV to always guarantee sufficient ventilation with a short response time.

Highlights

  • People flow rate means the number of people passing a specific location during a selected time interval

  • The zone population information can be further used in automatic control of environmental settings, such as demand-controlled ventilation (DCV) that responds to changes in the generation rate of indoor pollutant by adjusting ventilation rate [3,4]

  • The focus was on the five direction sensitive sensors that can be utilized in DCV

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Summary

Introduction

People flow rate means the number of people passing a specific location during a selected time interval. It is measured using a visitor counting sensor triggered by physical signals caused by the passing person such as visual appearance, heat emission, reflections of the body surface, or pressure against the floor [1]. The zone population information can be further used in automatic control of environmental settings, such as demand-controlled ventilation (DCV) that responds to changes in the generation rate of indoor pollutant by adjusting ventilation rate [3,4]. While a DCV that operates by monitoring the room’s carbon dioxide (CO2) level or temperature is always more or less retrospective, the use of visitor counting sensors enables a real-time response to changing occupancies.

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