A Framework on Health Smart Home Using IoT and Machine Learning for Disabled People
1S.L. Rakshanasri, J. Naren, Dr.G. Vithya, S. Akhil, K. Dinesh Kumar and S. Sai Krishna Mohan Gupta
The creation of accessible environments that promote independence, participation has been and remains a point of argument by and for disabled people. People with disabilities face large amount of hurdles and problems while trying to get help in the field of healthcare. In looking after disabled people the amount of services are limited, the treatment may be cost-effective and face many physical barriers. The paper presents a generic framework for an intelligent health smart home making the possibility for a person with disability to live in the comforts of home and be provided with healthcare services. The proposal of system is to develop an IoT based mobile gateway solution for Interactive Home wireless system, monitoring and control system and data acquisition system to display on mobile phone using S MS and email alert. The IOT applications developed in healthcare domain in smart home include mobile based control system, monitoring system and decision making system. Machine Learning is being employed to enable the IoT system to analyze sensor data, look for correlations and determine the best response to take. By detecting the values of the sensors, the temperature, smoke and presence of fire are found out in the environment and assuring the disabled person to handle any situation through IoT. Moreover information about patient’s heart rate, ECG and body temperature is collected and sent to a decision making system which contains fuzzy rules which calculates how frequently patient data are classified as normal and critical and also decides whether to store the data in database or forwarding to a caretaker to take immediate actions so that critical situations can be avoided.
Smart Environment, IoT, Machine Learning, Fuzzy Logic