A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
An IoT and 1D Convolutional Neural Network‐Based Method for Smart Building Energy Management
Implementing energy‐saving measures in buildings is essential for efficient energy management. The energy in a building is provided according to the number of occupants in the building. In this work, a deep learning‐based approach has been proposed for building occupancy detection and prediction using the signals from various sensors. The inputs used are temperature, light, CO 2 , and humidity. The input is given to the deep learning method to detect if the building is occupied or not. Then it determines the number of occupants in the building. The deep learning method used is a one‐dimensional convolutional neural network (1D CNN) method. The accuracy of the 1D CNN‐based method is 97.86% for detecting the building occupancy and 99.65% for predicting the number of occupants. Hence, the proposed method can be used to accurately detect and predict building occupancy and for building energy management.
An IoT and 1D Convolutional Neural Network‐Based Method for Smart Building Energy Management
Implementing energy‐saving measures in buildings is essential for efficient energy management. The energy in a building is provided according to the number of occupants in the building. In this work, a deep learning‐based approach has been proposed for building occupancy detection and prediction using the signals from various sensors. The inputs used are temperature, light, CO 2 , and humidity. The input is given to the deep learning method to detect if the building is occupied or not. Then it determines the number of occupants in the building. The deep learning method used is a one‐dimensional convolutional neural network (1D CNN) method. The accuracy of the 1D CNN‐based method is 97.86% for detecting the building occupancy and 99.65% for predicting the number of occupants. Hence, the proposed method can be used to accurately detect and predict building occupancy and for building energy management.
An IoT and 1D Convolutional Neural Network‐Based Method for Smart Building Energy Management
Zahira, Rahiman (editor) / Sivaraman, Palanisamy (editor) / Sharmeela, Chenniappan (editor) / Padmanaban, Sanjeevikumar (editor) / Swetapadma, Aleena (author) / Behera, Nalini P. (author) / Saran, Harsh (author) / Kumar, Saurav (author)
IoT for Smart Grid ; 291-300
2025-01-29
10 pages
Article/Chapter (Book)
Electronic Resource
English
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