An Intelligent Internet of Things (IoT) Sensor System for Building Environmental Monitoring
DOI:
https://doi.org/10.13052/1550-4646.15122Keywords:
Room occupancy monitoring, Internet of Things, Heterogeneous SensorAbstract
One of the world’s largest sources of energy dissipation is heating, ventilation, and air conditioning (HVAC), which accounts for 40% of total electricity use in the United States. The main challenge of current HVAC systems is that their operation is determined by a set of predefined setpoints regardless of the actual building occupancy status. This is wasteful, especially when no or fewer people occupy buildings, while these HVAC systems deliver more than enough fresh air. Occupancy-driven HVAC control is a promising strategy to improve the efficiency of HVAC systems. In this paper, we will address the next-generation sensor hardware design and explore new system architectures. We systematically investigate, design, and implement a lowcost, hybrid smart sensor platform for accurate occupancy counting towards energy-efficient buildings. Specifically, the proposed hardware architecture is wisely divided into two modules: main and gate monitoring modules. Five heterogeneous sensors are integrated into this architecture to collect richer building environmental parameters, including temperature, humidity. CO2, acoustic, and infrared signals. These sensor signals can be fused and analyzed for cross-correlation to increase the accuracy of building occupancy counting. The proposed systems have been implemented in breadboards and PCB boards. Experimental measurements have validated system functionality and performance.
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References
Energy, U. (2011). Buildings Energy Data Book, in, 2012.
Kamthe, A., Jiang, L., Dudys, M., and Cerpa, A. (2009, February).
Scopes: Smart cameras object position estimation system. In European
Conference onWireless Sensor Networks (pp. 279–295). Springer, Berlin,
Heidelberg
Erickson,V. L., Lin,Y., Kamthe,A., Brahme, R., Surana, A., Cerpa,A. E.,
Sohn, M. and Narayanan, S. (2009, November). Energy efficient building
environment control strategies using real-time occupancy measurements.
In Proceedings of the First ACM Workshop on Embedded Sensing
Systems for Energy-Efficiency in Buildings (pp. 19–24). ACM.
Emmerich, S. J., and Persily, A. K. (2001). State-of-the-art review of
CO2 demand controlled ventilation technology and application. Diane
Publishing Company
Yang, Z., Li, N., Becerik-Gerber, B., and Orosz, M. (2012). A nonintrusive
occupancy monitoring system for demand driven HVAC
operations. In Construction Research Congress 2012: Construction
Challenges in a Flat World (pp. 828–837).
Uziel, S., Elste, T., Kattanek,W., Hollosi, D., Gerlach, S., and Goetze, S.
(2013, October). Networked embedded acoustic processing system for
smart building applications. In Design and Architectures for Signal and
Image Processing (DASIP), 2013 Conference on (pp. 349–350). IEEE.
Huang, Q., Ge, Z., and Lu, C. (2016). Occupancy estimation in smart
buildings using audio-processing techniques. In International Conference
on Computing in Civil and Building Engineering (pp. 1413–1420).
Huang, Q. (2018). Occupancy-driven energy efficient buildings using
audio processing with background sound cancellation. Buildings, vol. 8,
no. 6, pp. 1–16, 2018.
Balaji, B., Xu, J., Nwokafor, A., Gupta, R., and Agarwal, Y. (2013,
November). Sentinel: occupancy based HVAC actuation using existing
WiFi infrastructure within commercial buildings. In Proceedings of the
th ACM Conference on Embedded Networked Sensor Systems (p. 17).
ACM.
Huang, Q., Mao, C., and Chen, Y. (2017).Acompact and versatile wireless
sensor prototype for affordable intelligent sensing and monitoring
in smart buildings. In International Workshop on Computing in Civil
Engineering, pp. 155–161, 2017.
Lattice iCEstick evaluation kit, available at http://www.latticesemi.com/
icestick
Rodriguez, K., Whetstone, N., Habel, S., Lu, C. (2017). A Smart IoT
Prototype for Accurate People Counting Towards Energy Efficient Smart
Building. In Design Automation Conference, Austin, Dallas, United
States.
Infrared emitter and receivers, https://www.sparkfun.com/products/241
Wi-Fi component, https://www.sparkfun.com/products/13231
Arduino Nano, https://store.arduino.cc/arduino-micro-without-headers