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Optimized Home Appliances Management Using Random Forest Algorithm

  • Unique Paper ID: 163941
  • Volume: 10
  • Issue: 12
  • PageNo: 520-522
  • Abstract:
  • In this project, we propose an optimized home appliances management system using Random forest algorithm techniques. The system integrates various sensors LDR, IR, DHT11 and Gas sensor. These sensors are interfaced with an Arduino microcontroller to collect environmental data from the home environment. The LDR sensor measures ambient light levels, the IR sensor detects human presence, and the gas sensor monitors air quality for potentially hazardous gases. The DHT11 sensor captures temperature and humidity data. The sensors data is transmitted to Random Forest algorithm implemented on a computer or microcontroller board. The Random Forest algorithm to analyze the sensor data patterns and make decisions regarding the operation of home appliances. The goal is to optimize energy consumption while maintaining comfort and safety within the home environment. The algorithm evaluates the sensor data and determines whether to turn on or off home appliances. For instance, the system may automatically adjust lighting levels based on ambient light conditions sensed by the LDR, or activate the CPU fan when the temperature exceeds a certain threshold detected by the DHT11 sensor.
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  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 520-522

Optimized Home Appliances Management Using Random Forest Algorithm

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