The design of the mobile application allows a graphical display of the activities in the house. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. Our work uses a camera to capture images of objects triggered by their motion being detected. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images.
WHAT SENSOR BASED VALUE SHOULD I USE MACS FAN CONTROL ANDROID
The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application.
This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. The smart home is now an established area of interest and research that contributes to comfort in modern homes.
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