## 1 Introduction  
Emerging as a game-changing technology, Wireless Sensor Networks (WSNs) have the ability to revolutionize numerous industries and applications. The \"sensor nodes\" that comprise these networks are small autonomous devices that can detect, process, and transmit data wirelessly. Wherever conventional wired networks are too costly or impossible to implement, WSNs have found use, including in environmental monitoring, healthcare, industrial computerization, military shadowing, and many more. One major advantage of WSNs is their ability to gather data from inaccessible or harsh locations. Dense networks formed by several sensor nodes can provide detailed, real-time data about the monitored area. Efficiency and safety can be enhanced in a variety of applications with the use of these data for decision-making, monitoring, and control. Despite all the benefits, WSNs still have a long way to go before they can reach their maximum potential. Problems arise, for example, when the processing and data transfer capacities of individual sensor nodes are inadequate. Energy efficiency is a major concern in WSNs since sensor nodes' batteries have limited capacity, and it is impossible to charge or replace them frequently in many deployment situations. The necessity for efficient and reliable communication protocols is another obstacle with WSNs. The design of the protocols that let sensor nodes communicate with one another and with a central base station is a key factor in the network's overall success. Verifying the dependability and efficiency of communication in WSNs requires fixing problems with routing, data aggregation, and congestion control. A lot of work has gone into improving the efficiency and dependability of WSNs in recent years. Data processing using machine learning algorithms, optimization methods for reduced energy consumption, and new communication protocols for enhanced network efficiency are all examples of what is meant here. When these problems are solved and these innovations are used, WSNs could change data collection, processing, and usage for many different things. Figure 1 represents the basic structure of an IoT-based WSN. The integration of the Internet of Things (IoT) and WSNs has revolutionized the field of sensing, communication, and data collection in various industries. By combining IoT with WSNs, the communication capabilities of these networks can be enhanced, making them more intelligent and efficient in a wide range of applications including smart cities, healthcare, agriculture, and industrial automation. IoT-based WSNs play a critical role in modern technological ecosystems, particularly in the context of smart environments, industry 4.0, and automation. These networks consist of spatially distributed autonomous sensors that monitor physical or environmental conditions such as temperature, humidity, pressure, and motion, and transmit the data to a central hub for processing. The integration of WSNs with the IoT extends their functionality beyond simple data collection to include remote monitoring, control, and decision-making capabilities. This enables real-time interaction between physical and digital systems across various domains, such as healthcare, agriculture, smart cities, and industrial automation. IoT-based WSNs leverage various communication protocols, including Wi-Fi, Bluetooth, Zigbee, and LoRa, to ensure seamless connectivity and data transfer across devices, even in remote or challenging environments. The scalability and flexibility of these systems allow for the integration of a wide range of sensors and actuators, making them adaptable to diverse applications. However, challenges such as energy efficiency, security, and data privacy remain critical considerations. The limited battery life of sensor nodes requires the development of energy-harvesting techniques or optimized communication protocols to extend network longevity.