A New Classification of Target Coverage Models in WSNs, Survey and Algorithms and Future Directions

dThe importance given to addressing the k-target coverage problem (k >= 1) in the wireless sensor network, makes problem-solving spawn diverse domains, such as medicine (chronic disease monitoring and heartbeat monitoring), atmospheric events, such as (monitoring and measuring temperature, humidity, fog percentage, and pressure), and other domains. This importance has led to the proposal of various classifications of target coverage. This paper proposes a target coverage algorithm based on finding the disjoint sensor covers (DSC) to maximize coverage with minimum energy consumption over the lifetime of the sensor nodes used, and a new classification of linear and nonlinear target coverage based on deployment type, DSC and targets number) that enhances the advantages of this type of coverage in WSNs for various applications, particularly in the fields of medicine, biology and drug control.