Natural disasters affect millions of peoples every year around the globe. These include flood, fire, earthquake, windstorm etc. These disasters are different in nature but in the end, they cause damage to human lives, economy, properties and health. Diversity in the nature of these calamities also requires different ways to monitor them and to mitigate the damages they cause. Floods, among other disasters, are the most common hazards that leave nothing but destruction behind. In addition to an effective evacuee plan, forecast information and keeping the communication up even when the flood is at its climax, helps the citizens survive through a flood situation. Thus damages can be reduced significantly and it also helps to seek aid, food and shelter in a better way. Furthermore, such information serves as a learning source and helps planning ahead for the future floods.
Smart Flood Monitoring System-of-Systems (SoS) is a flood monitoring and rescue system. It collects a large amount of information from weather and flood onlookers and observers. This information is then made available as alerts to the citizens before the flood, to plan ahead and during the disaster for getting help and to support rehabilitation process. System also maintains communication with the authorities for disaster management, social services and public utilities (collectively referred to as ?emergency responders?) to synchronize their support and rescue efforts with the community needs. The proposed approach satisfies three conditions imposed by the definition of SoS i.e. autonomy, geographic distribution and constant evolution of components. Main focus of the proposal is to specify, design and formally verifying a smart SoS model of flood monitoring to communicate the right information to the right people at the right place well in time. Smart Flood Monitoring System-of-Systems (SoS) is verified by constructing Timed Coloured Petri Nets (CPN) using CPN Tools 4.0.0. Model checking is done by specifying the safety properties in Finite Space Processes (FSP) and analyzing them by Labeled Transition System Analyzer (LTSA) 3.0. This formal verification will ensure the correctness properties of the proposed model.