Development of an Embedded System for Building System Management Based on PV-Powered

Year 2021, Volume: 9 Issue: 3, 249 - 254, 30.07.2021

Hussein Ali , Ergün Erçelebi

https://doi.org/10.17694/bajece.933353

Abstract

As complexity and the type of electrical applications perpetually expands, monitor and control will require new systems which are based on some features in such feature of self-powered and distantly management. Building management systems (BMSs) are developed as efficient solutions to monitor and control users electrical and mechanical applications. A BMS employs cheap sensors and a real-time module to create prior knowledge about the climate inside the building. As a result, these features give some attractive advantages in taking a precise decision and managing vital operations of electrical applications. In this paper, a Raspberry Pi as minicomputer for collecting information from server room or data centre for detection the existence of human, temperature and humidity sensor and gas sensors to control ventilation systems, Arduino platform is responsible for receiving sensors signal and control actions according to the statues in the server room. While the Xbee protocol has been used to transmit data from the sensing node (Raspberry PI3) to mentors and control nodes (Arduino mega2560). The prototype design has been verified experimentally.

Keywords

Building management systems, Power Saving, Smart Power System, Raspberry PI 3, XBee modules. .

References

• [1]S. V. R. Hellriegel, M. L. Jaena, B. D. Koblenz, D. L. Anderson, D. Driggers, and J. R. Hampton Walker Haddock, “Data center.” Google Patents, Aug. 02, 2011
• [2]Q. N. Do and T. C. Le, “Low Power Embedded System Design Using Code Compression,” no. September, pp. 0–4, 2015.
• [3]F. Emnett and M. Biegel, “Power reduction through RTL clock gating,” SNUG, San Jose, pp. 1–11, 2000.
• [4] D. Flynn, R. Aitken, A. Gibbons, and K. Shi, Low power methodology manual: for system-on-chip design. Springer Science & Business Media, 2007.
• [5] J. Lee, B.-G. Nam, and H.-J. Yoo, “Dynamic voltage and frequency scaling (DVFS) scheme for multi-domains power management,” in 2007 IEEE Asian Solid-State Circuits Conference, 2007, pp. 360–363.
• [6] W. Li, T. Logenthiran, V.-T. Phan, and W. L. Woo, “Implemented IoT-based self-learning home management system (SHMS) for Singapore,” IEEE Internet Things J., vol. 5, no. 3, pp. 2212–2219, 2018.
• [7] U. R. Pi and R. P. M.- B, “Internet of Things Based Home Security,” 2018 Fourth Int. Conf. Comput. Commun. Control Autom., pp. 1–6.
• [8] P. P. Ricci, M. Donatelli, A. Falabella, A. Mazza, and M. Onofri, “Evolution of the Building Management System in the INFN CNAF Tier-1 datacenter facility,” JPhCS, vol. 898, no. 8, p. 82005, 2017.
• [9] T. Benson, A. Anand, A. Akella, and M. Zhang, “Understanding data center traffic characteristics,” ACM SIGCOMM Comput. Commun. Rev., vol. 40, no. 1, pp. 92–99, 2010.
• [10] M. K. Patterson, “The effect of data center temperature on energy efficiency,” in 2008 11th Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, 2008, pp. 1167–1174.
• [11] S. Blaifi, S. Moulahoum, I. Colak, and W. Merrouche, “Monitoring and enhanced dynamic modeling of battery by genetic algorithm using LabVIEW applied in photovoltaic.
• [12] Halfacree, G., & Upton, E. (2012). Raspberry Pi user guide. John Wiley & Sons.‏system,” Electr. Eng., vol. 100, no. 2, pp. 1021–1038, 2018.