Using IoT-Implement Intensive Care for Air Conditioners with Machine Learning


  • Nripendra Narayan Das Professor, Department of Information Technology, Manipal University Jaipur, Rajasthan, India
  • K. Somasundaram Professor, Institute Of Information Technology, Saveetha School Of Engineering, Simats, Chennai, Tamil Nadu, India
  • S. Hemamalini Associate Professor/ CSE, Panimalar Institute of Technology, Chennai, Tamil Nadu, 600123, India
  • K. Valarmathia CSE, Panimalar Engineering College, Chennai, Tamil Nadu, India
  • G. Nagappan Professor & Head, Department of Computer Science and Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, 600127, India
  • S. Hemalatha Professor, Department of Computer Science and Engineering, Panimalar Institute of Technology, Chennai, Tamil Nadu, 600123, India
  • Kamal Gulati Associate Professor, Amity University, Noida, Uttar Pradesh, India


Internet of Things, machine learning, home automation


This study suggests a survey on air conditioner intensive care to check defects As the globe becomes increasingly technologically advanced, various electronic application gadgets are invented and used by individuals. New technological devices are infiltrating our personal life at an increasing rateIt results in the development of an increasing number of electronic gadgets. This necessitates gadget maintenance; otherwise, the devices may be damaged. These electrical gadgets can be serviced by a device expert. The average individual is incapable of anticipating and resuming the functioning of electrical equipment. However, the full scenario, as well as the device's specialist, cannot be attempted in a timely manner. These factors need the purchase of a new equipment. This suggested project will provide a method for preventing electrical equipment failure and replacement. This project uses the Machine language approach to analyses the device's condition and monitoring on a daily basis, comparing it to predetermined machine parameter values. If a difference is discovered between the estimated and predefined state, the machine must be fixed before it fails. The suggested technology calculates the variance and alerts the invented firm and the end user, allowing them to take action before the equipment malfunctions. The Internet of Things (IoT) was used in conjunction with a machine learning algorithm to communicate between gadgets and the enterprise or user. The benefit of this job is that it prevents machine failure, extends the machine's life, and avoids expert repairs that are incorrect. Because it takes a long time to monitor and find defects, the idea of machine learning is employed, which entails the study of machines in order to detect errors quickly. This project shows a simple home-controlled air conditioner system with an IoT device that enables for periodic defect monitoring.


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Architecture diagram




How to Cite

Narayan Das, N. ., Somasundaram, K. ., Hemamalini, S. ., Valarmathia, K. ., Nagappan, G. ., Hemalatha, S. ., & Gulati, K. . (2023). Using IoT-Implement Intensive Care for Air Conditioners with Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 11(3s), 194–203. Retrieved from



Research Article