Performance Enhancement of Passive Infrared (PIR) Sensor in Internet of Things (IOT) Network for Energy Management

Abstract

The greater demand foe energy in every sector, across the nation leads to an imbalance in production and consumption of energy. According to the Central Electricity Authority’s report, India is the third largest primary user of energy in the world. The energy utilization in India is upto 847 billion units in the first quarter of 2023 which has increased by 8.5% from the previous year. This exponential growth of consumption in developing nations like India, has raised concerns as it involves risks to the renewable and natural resources. The large scale sectors like commercial, residential, health and defense require a large amount of energy with 65% of the total utilized by the commercial and residential ones. The major issues of these sectors are the involvement of heating, ventilation, and air conditioning (HVAC) systems and electrical loads with high energy consumption. To manage the energy consumption of these sectors, an energy management system (EMS) comes into the picture. The EMS orchestrates and oversees energy governance and monitoring operations through incorporating smart technology and components. The technologies reported in implementing EMS are expensive, less secure, inefficient, and less compatible to all the other systems. In addition, if the managing of huge amounts of data is continued using these innovative technologies then it’s full potential cannot be exploited due to the chances of loss of data, limiting the efficiency of the system. Although, the extensive deployment of EMS in different sectors have proposed with unlimited innovative technology to overcome the challenges involved, cloud computing empower the Internet of Things (IoT) is away better technology. The smart EMS design does not need complex architecture or expensive components and offers more security. In this thesis, IoT cloud-computing based EMS is designed to manage the huge amount of energy consumed in the residential sectors and offers a significant reduction in the use of energy. This approach not only simplifies the system architecture and reduce cost but also improves security and compatibility with other systems. The study is centered on a standard sized room equipped with an HVAC system, and electrical loads. The system implemented makes use of sensors, wireless technology and IoT platform. There are two stages of the proposed design, first is the hardware set-up: real time data monitoring stage and the second is software implementation: energy and management and reduction stage. Initially, the best suitable combination of smart sensor, wireless technology, and IoT platform for real time occupancy and weather monitoring are explored. A passive infrared (PIR) sensor is used for motion detection in the room and a digital humidity temperature 11 (DHT-11) sensor captures the indoor temperature and relative humidity. PIR mathematical model is developed and different parameters are investigated. It is observed that sensor performance mainly relies on sensitivity and efficiency. Hence, the sensitivity enhancement method is proposed implying two main parameters, rate of absorption of infrared (IR) with respect to distance (α) and rate of absorption of IR with respect to sector angle of the lens traversed (γ). The best sensitivity of 14.7647 V-m2/W is achieved by exploring the appropriate combination of α and γ values. The model is further extended by implementing an innovative signal conditioning technique to improve the efficiency to 95%. The study also explains the variation in the output voltage, power and current flow through the system. Moreover, while sensing the real time data through the PIR sensor using IoT platform, accuracy for transferring data in the IoT-cloud server and back plays a major role. The investigation is done to increase the accuracy by using the accuracy control method. The extracted data is compared with the ground truth values, achieving an accuracy of 85.5%. Furthermore, the DHT-11 sensor is chosen over other temperature, humidity sensor because of its low cost, better accuracy, sensitivity, and low power consumption. Hardware set-up is deployed in the room comprising of the PIR and DHT-11 sensors, Node- MCU, and Thing-speak IoT platform for real time monitoring. The PIR records the presence and absence of an individual in the room, while DHT-11 captures the room temperature and humidity. The Thing-speak is an open source IoT-cloud computing platform to analyze, monitor and view the statistics of extracted information. After, a thorough study of the values, an algorithm for energy reduction is proposed to scale down the energy consumption for future use. The algorithm is applied to the HVAC system and an electrical load (capacitive fan) and the energy utilization is managed and calculated. Moreover, the results of the system show the better reduction in the energy utilization of both of the devices. The proposed system is superlative to already existing technologies like SED with a 72.34% reduction in energy consumption. Hence, the research presented in the thesis involves the study of the parameters required for the better working of the smart PIR and DHT-11 sensors. The investigation is done on the sensitivity and efficiency enhancement of the PIR sensor and key parameters are kept in mind for choosing the temperature and humidity sensor which is further used in the implementation of IoT Cloud Computing Energy Management System. Moreover, comparative results are also shown to make the proposed system a great scope for a commercial and residential sectors where energy management is a key issue.