Intelligent Monitoring System for Automatic Air Conditioning System
In order to improve indoor air quality, optimize energy consumption and avoid the accidents due to gas leakage, this paper proposes an intelligent air conditioning system that integrates several sensors such as DHT11, PIR sensors, MG6 Gas sensor and PMS7003 sensor and control mechanisms. An Arduino Mega, the system's central component, synchronizes data from several sensors to efficiently control the air conditioner and other linked equipment. This system keeps track of how many people enter and leave the space, enabling the air conditioning system to modify its settings in real time according to occupancy. When the room is empty, this feature saves energy. If gas leakage is present, system notifies users through a buzzer and turn off the AC. Many users often forget to clean their AC filters regularly, which can lead to reduced efficiency, higher energy consumption, and poorer air quality. Our innovative AC system addresses this common issue. Once the dust level crosses a predefined threshold, the system triggers a clean filter alert, reminding to act before it affects performance. Also, the air conditioner kicks on to cool the room if the outside temperature is high and the inside temperature is higher than an acceptable level. In contrast, the air conditioner is shut off to avoid needless cooling if the inside temperature is low. A display unit shows temperature, humidity, occupancy, gas levels, and dust concentration. This integrated technique automatically modifies the system's operation based on conditions, ensuring not only a more hygienic and comfortable environment but also improved energy efficiency
Authors
- P. Manikandan (ORCID: https://orcid.org/0000-0002-5737-0235)
- P Reddy (ORCID: https://orcid.org/0009-0008-3613-8235)
- C. Swedheetha
- S. Kumar
- Rajat Mohan
- Pachabotla Adithya Sri Sai
Institutions
- Velammal Medical College Hospital and Research Institute (IN)
- Kalasalingam Academy of Research and Education (IN)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/icicnis64247.2024.10823121
- Citations
- 2
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.66