A Cognitive Wireless Sensor Network (CWSN) employs AI for autonomous optimization in smart cities, industry, military, healthcare, and animal protection, enhancing sensor networks with adaptive intelligence. The portrayed method frames the usage of LEACH in CWSN to enhance energy efficiency and improve network life span. The cluster heads (CHs) are chosen using fuzzy logic, which provides a way to make wise choices even in the face of inaccurate data. While selecting a CH, a number of parameters considered are residual energy, distance from the base station (BS), and angle to the BS. In this proposed method, the base station assumes a vital role, taking on responsibilities such as selecting CHs for various areas, assigning nodes to specific zones, calculating distances between nodes and cluster centers, and determining node angles. The proposed protocol effectively balances energy consumption, improving CWSN performance and maximizing throughput, minimizing delay compared to traditional algorithms for environmental monitoring applications.