Optimized Landmine Detection Simulation Using Cellular Automata

In today's world, the detection and disposal of landmines is one of the most difficult and intractable problem faced in ground conflict. The presently used techniques of detection mainly work on the content of metal in mines which takes more time in searching the landmines. The aim is to detect those mines which contain less metallic contents. So, the points which are taken into account in developing the model for searching the landmines in optimal time are checking the metal of landmine with battery content, heat generation of those portions of land where the landmines exists, determine the optimized path from source to destination along with the detection of landmines and generation of transition rule of cellular automata. Therefore, we develop a deterministic algorithm with the help of an optimization technique i.e. Particle Swarm Optimization (PSO) and Cellular Automata (CA) which will optimize the search of landmines, searching both locally and globally, in much less time as compared to any other method and also limiting the chances of PSO of getting trapped in the local optima. The main work is to simulate the algorithm to solve the problem of detection of landmines.