India is vulnerable to natural disasters such as floods, droughts, cyclones, earthquakes, landslides, etc. Every year there is an increase in the frequency and intensity of disasters. Every year about 20 disasters hit India and around 2,000 lives are lost. There is a lack of a recognized smart building risk assessment methodology and an efficient evacuation plan. The use of a smart building sensor framework and behavioral model integrated with risk analysis can provide a better evacuation. According to the National Disaster Management Authority, around 12% of the total land area is exposed to floods, and 68% of the land is vulnerable to drought, landslides, and avalanches. 58.6% of the landmass is earthquake-prone prone and tsunamis and cyclones are a regular phenomenon for 5700km of the 7516km long coastline. This made the position of India amongst the top disaster-prone countries. Natural disasters adversely affect humans as well as threaten India’s economic development. Thus disaster risk management finds its importance in a country like India. Smart buildings use automated processes to control the building’s operations including heating, ventilation, air conditioning, lighting, security, and other systems. With the help of sensors and machine learning, use of energy can be controlled without affecting the comfort level. Data from the same sensors along with the environmental factors can be used for risk analysis. The environmental factors considered are, which are influencing the occurrence of the disaster or increasing the intensity of the disaster. Once the risk analysis is done we get the risk level. According to the risk level, different levels of warning can be made and can provide a better evacuation.
