International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 05 | May 2025
p-ISSN: 2395-0072
www.irjet.net
IoT-Driven Energy Efficiency in Commercial Spaces: Integrating Occupancy Detection, Cloud Automation, and Edge Computing V. A. Dahore1, Dr. Prof. S. V. Pattalwar2, Prof. V. R. Raut3 1Digital Electronics, PRMITR Badnera, Amravati, Maharashtra
2HoD Electronics & communication, PRMITR, Badnera, Amaravati, Maharashtra 3 Professor , PRMITR, Badnera, Amaravati, Maharashtra ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This study proposes an IoT-based energy
Area Network) and Zigbee [2]. The application layer utilizes cloud computing platforms, including AWS IoT (Amazon Web Service IoT) and Microsoft Azure, to automate energy management systems.
management system for commercial meeting rooms, integrating Passive Infrared (PIR) sensors, Raspberry Pi edge computing, and Salesforce Cloud for real-time occupancy monitoring and automation. The methodology employs Python scripts to process sensor data, trigger HVAC/lighting controls, and transmit metrics to Salesforce for dashboard visualization. Results demonstrate a 28% reduction in energy consumption and 92% accuracy in occupancy detection, validating the system’s efficacy in reducing operational costs and carbon footprints.
A pertinent example can be observed in the implementation at The Edge in Amsterdam, where 28,000 sensors have been utilized to attain energy savings of approximately 70% by dynamically adjusting lighting and HVAC (Heating Ventilation and Air Conditioning) systems based on real-time occupancy data [3]. Furthermore, Google’s Nest Labs has documented a 12% decrease in HVAC expenditure owing to the integration of machine learning algorithms.
Key Words: IoT, energy efficiency, PIR sensors, Salesforce Cloud, edge computing, Raspberry Pi.
2.2 Sector-Specific Implementations
1.INTRODUCTION
The healthcare sector has witnessed a 25% reduction in HVAC energy consumption due to the deployment of IoT systems in hospitals, all while maintaining patient comfort standards. In a similar vein, academic institutions, such as the University of California, Berkeley, have adopted IoTenabled lecture halls, which have successfully achieved a 30% reduction in energy waste through occupancy-triggered automation [4]. In the retail domain, Walmart’s implementation of motion-sensitive LED systems has resulted in an annual energy saving of 1.4 terawatt-hours (TWh) [5].
The emergence of the Internet of Things (IoT) signifies a notable enhancement in the management of sustainable building practices, facilitating extraordinary control over energy consumption in commercial settings. Buildings contribute approximately 40% of global carbon emissions, making the adoption of IoT-enabled systems vital for achieving climate objectives delineated in the Paris Agreement and the United Nations Sustainable Development Goals (UN SDGs). This review examines the evolution of IoT architectures, sensor technologies, and cloud platforms, with a specific focus on their efficacy in optimizing energy usage in meeting rooms, which frequently demonstrate operational inefficiencies.
2.3 Challenges in Legacy Systems Legacy HVAC and lighting systems frequently exhibit adaptability limitations, leading to the phenomenon of "phantom loads" in unoccupied spaces. Studies indicate that approximately 35% of meeting rooms continue to consume power despite being unoccupied, primarily due to outdated booking methods [6]. The integration of real-time sensor networks alongside predictive shutdown protocols via IoT solutions effectively mitigates these inefficiencies.
2. IoT & ENERGY EFFICIENCY IN COMMERCIAL SPACES 2.1 IoT Architectures and Frameworks IoT system architecture is generally structured into three distinct layers: the perception layer, the network layer, and the application layer. Each layer plays a critical role in ensuring seamless data flow from sensors to processing platforms [1]. The perception layer is composed of a variety of sensors, including passive infrared (PIR) and carbon dioxide (CO₂) detectors, as well as actuators such as smart HVAC systems and automated lighting solutions. Connectivity within the network layer is achieved through low-power communication protocols, like LoRaWAN (Long Range Wide
© 2025, IRJET
|
Impact Factor value: 8.315
3. OCCUPANCY DETECTION TECHNIQUES 3.1 Passive Infrared (PIR) Sensors PIR sensors are commonly utilized for occupancy detection owing to their low cost (under $10 per unit) and minimal energy consumption (between 0.1 and 1 watt). Gupta et al.
|
ISO 9001:2008 Certified Journal
|
Page 842