Abstract

Wireless Sensor Networks (WSNs) are an emerging technology that has gained immense popularity due to its ability to provide real-time data from remote locations. In recent years, WSNs [1] have been widely adopted in various applications, including environmental monitoring, healthcare, agriculture, smart homes, and smart cities. This paper presents an abstract on the current and future trends of WSNs. One of the significant trends in WSNs is the development of energy-efficient protocols and algorithms. Researchers are exploring new techniques to minimize energy consumption by sensors, which directly impacts the network's lifetime. Another trend is the integration of WSNs with other technologies, such as the Internet of Things (IoT), cloud computing, and big data analytics, to enable more advanced applications. Another trend is the use of Machine Learning (ML) and Artificial Intelligence (AI) techniques to analyze the data collected by WSNs. These techniques can be used to identify patterns and anomalies in the data, which can be used to improve the efficiency and accuracy of the system. The future of WSNs looks promising, with new technologies emerging that will enhance their capabilities. One of the upcoming trends is the development of Low-Power Wide Area Networks (LPWANs), which will enable long-range communication with low power consumption. This technology will be particularly useful in smart cities and industrial applications. The development of autonomous WSNs is another future trend. These networks will be capable of self-organization, self-configuration, and self-management, reducing the need for human intervention. This will result in more efficient and reliable networks. WSNs are an essential technology that has the potential to revolutionize various industries. As the technology continues to evolve, it is essential to keep up with the latest trends to ensure that WSNs remain at the forefront of innovation.

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