This paper presents a solution to the coverage problem in wireless sensor networks, where the goal is to determine whether every point in the service area is covered by at least k sensors. The problem is formulated as a decision problem, and the solution is based on checking the perimeter coverage of each sensor's sensing range. The sensing range of each sensor can be a unit disk or a non-unit disk. The proposed solution is efficient and can be easily translated into distributed protocols. The algorithm runs in polynomial time, with a complexity of O(nd log d), where n is the number of sensors and d is the maximum number of sensors whose sensing ranges may intersect a sensor's sensing range. The solution is applicable to both unit-disk and non-unit-disk coverage problems. The results can be used to determine insufficiently covered areas, conserve energy in redundant sensors, and support hot spots. The paper also discusses several applications and extensions of the coverage problem, including discovering insufficiently covered regions, power saving in sensor networks, hot spots, and extension to irregular sensing regions. A software tool is provided to implement the proposed algorithms. The paper concludes that the proposed solution is efficient and can be used to solve the coverage problem in wireless sensor networks.This paper presents a solution to the coverage problem in wireless sensor networks, where the goal is to determine whether every point in the service area is covered by at least k sensors. The problem is formulated as a decision problem, and the solution is based on checking the perimeter coverage of each sensor's sensing range. The sensing range of each sensor can be a unit disk or a non-unit disk. The proposed solution is efficient and can be easily translated into distributed protocols. The algorithm runs in polynomial time, with a complexity of O(nd log d), where n is the number of sensors and d is the maximum number of sensors whose sensing ranges may intersect a sensor's sensing range. The solution is applicable to both unit-disk and non-unit-disk coverage problems. The results can be used to determine insufficiently covered areas, conserve energy in redundant sensors, and support hot spots. The paper also discusses several applications and extensions of the coverage problem, including discovering insufficiently covered regions, power saving in sensor networks, hot spots, and extension to irregular sensing regions. A software tool is provided to implement the proposed algorithms. The paper concludes that the proposed solution is efficient and can be used to solve the coverage problem in wireless sensor networks.