Implementation of Edge Computing for Optimizing Sensor Data Collection in Smart Buildings
Abstract
The development of the Internet of Things (IoT) has driven the implementation of smart buildings that rely on real-time sensor data collection and analysis. However, cloud computing-based systems often face problems of high latency and large network loads. This research implements an edge computing architecture to optimize sensor data collection in smart buildings. A prototype was built using edge nodes (Raspberry Pi) that process data from temperature, humidity, light, and motion sensors locally before sending it to the cloud. Test results show that edge computing can reduce latency by up to 45% and reduce data traffic to the cloud by 60%, while also improving the energy efficiency of sensor devices. Thus, edge computing has been proven to effectively improve the performance and efficiency of data collection systems in smart buildings
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DOIAuthor Biographies
Universitas Islam Kebangsaan Indonesia, Bireuen Regency, Aceh Province, Indonesia.
Universitas Teuku Umar, West Aceh Regency, Aceh Province, Indonesia.
Universitas Amir Hamzah, Deli Serdang Regency, North Sumatra Province, Indonesia.
Universitas Muhammadiyah Asahan, Asahan Regency, North Sumatra Province, Indonesia.
Universitas Islam Kebangsaan Indonesia, Bireuen Regency, Aceh Province, Indonesia.
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