Both connectivity and coverage are considered as the basic performance standards of the service yielded through a Wireless Sensor Network (WSN). Sensing field’s monitoring quality is represented through coverage. So, coverage represents the quality of tracking of the sensing field through the sensors. Connectivity exhibits the quality of the information delivery along with the sensor nodes, or to the base station. This paper aims for pre-estimation for the sensor numbers that are to be placed in an adverse situation for achieving required coverage. This paper promotes -coverage and -connectivity models that focuses on multipath effects as well as shadowing fading’s combined effect. The value of differs for different types of applications. For measuring the coverage and connectivity probabilities, in shadowing as well as multipath fading presence, a mathematical model is obtained. Moreover, the coverage and connectivity probability derivations which are derived with the help of lognormal shadowing fading as well as Rayleigh fading are approved through the deployments of nodes utilizing Poisson distribution. The simulation section of this paper clearly shows that coverage and connectivity are dependent on the density of node, fading parameters like the standard deviation, and path loss exponent. The sensing model proposed by us is proved to be more appropriate for realistic environment as sensor’s ideal quantity necessary in order to attain desirable coverage in fading conditions.