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The purpose of this work is to develop a prototype of flood alerting system (FAS) based on the Internet of Things (IoT) to save the lives and property by alerting the people about flood. The proposed system can permit detection and evaluation of threating events to take place before it hits a network or community.

Connecting water bodies or water channels to the cities is a sign of development and growth, but sometimes when these connected water channels gets overfilled due to some reasons then they can create horrendous situation, one of such situations is flood. Hence, there is a need to find a way, in order to alert when there will be flood-related conditions and to predict if there are any such conditions in near future. In this work, a model based on FAS, that can alert when flood-related conditions are there, is proposed. Mathematical modelling of the model is done through the Markov process to obtain the state transition probabilities, and these probabilities are solved by Laplace transformation. The performance of the proposed system is affected by good or bad working of its components. Thus, the performance characteristics are expected in terms of component failure rates. Failure and repair rate of FAS's components follow exponential and general distribution.

Using the proposed Markov model, performance characteristics of the model like availability, reliability, mean time to failure (MTTF), profit and sensitivity have been calculated and explored by taking numerical illustration. Graphical representation of performance characteristics is done to make the results more understandable.

This work presents a Markov process-based reliability model of FAS, which provides the information about failures and working of the system's components. Also, it provides information about components and failures which majorly affect the system reliability.