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In recent years, Wireless Sensor Networks (WSN) have skilled quick development and great growth due to its extensive uses across a range of industries, such as healthcare, manufacturing, military, and so on. WSN most commonly utilizes mobile sinks for reducing the energy-hole problem during collection of data from the randomly dispersed sensor nodes. The mobile sinks in WSN should be placed in such a way that it extends the lifetime of WSNs. This paper proposes a model named Deep Q Net is utilized for the placement of mobile sink. Initially, the cell network is transformed by the Voronoi partition, and the network is partitioned into various clusters. Then Cluster Head (CH) is selected by employing Deep Embedded Clustering (DEC). The optimal placement of the mobile sink is carried out using the adjacency-based cell score, which effectively places the mobile sink using the constrained factors Afterward, to detect the location of the mobile sink, an adjacency-based cell score is utilized, which is done by employing various factors, like fairness, distance, and predicted energy. Next, energy prediction for the detection of mobile sink is performed using Deep Q Net. Furthermore, Proposed Deep Q Net obtained a minimum distance with the value of 26m whereas normalized fairness, energy, normalized throughput, and network lifetime acquired a maximum value of 67, 0.006J, 81, and 92S respectively.