Wireless sensor networks (WSNs) are advancing scientific pursuits and enhancing productivity in various sectors such as manufacturing, agriculture, construction, and transportation. The exponential growth in semiconductor technology has led to miniaturization and increased computing power, enabling the development of low-power, inexpensive communication devices that can be densely deployed to sense and process physical phenomena. These devices, combined with system software, form the Internet of Things, allowing for detailed instrumentation and data collection. WSNs face challenges due to resource constraints, energy limitations, and harsh environmental conditions. They must operate for extended periods with minimal energy consumption, often turning off most components when not in use. The dense deployment of nodes requires efficient networking protocols to manage connectivity and interactions. Despite these challenges, WSNs offer significant opportunities in environmental monitoring, structural health monitoring, condition-based maintenance, and other applications. Environmental monitoring, for example, involves collecting readings over large volumes of space to study internal variations. WSNs can provide simultaneous measurements at multiple points, spanning elevation and radial directions, over prolonged periods. This data helps in understanding growth dynamics, water intake, and nutrient transport in ecosystems. Motion monitoring applications, such as condition-based maintenance, use WSNs to detect wear and fatigue in structures like machines, bridges, and buildings. By performing local processing and continuous data transmission, WSNs can improve plant performance and reduce costs. The technology behind WSNs includes microprocessors, power sources, and sensors. Microcontrollers operate on low power, and MEMS sensors can sense a wide range of physical phenomena efficiently. Microradios enable wireless communication, though energy consumption remains a significant challenge. WSNs are built using layered networking protocols that manage physical radio devices, link layers, and packet layers. Data dissemination and collection are achieved through flooding protocols and tree formation, with reliability enhanced by disruption-tolerant networking approaches. Power and bandwidth conservation are crucial, with techniques such as local data processing, aggregation, and compression employed to optimize energy usage. Privacy concerns arise in settings with multiple potential users, requiring careful management of data collection and dissemination. The future of WSNs promises smaller, more integrated devices that will become integral to manufacturing processes and environmental monitoring. This evolution will require new information technology architectures and programming languages to fully realize their potential.Wireless sensor networks (WSNs) are advancing scientific pursuits and enhancing productivity in various sectors such as manufacturing, agriculture, construction, and transportation. The exponential growth in semiconductor technology has led to miniaturization and increased computing power, enabling the development of low-power, inexpensive communication devices that can be densely deployed to sense and process physical phenomena. These devices, combined with system software, form the Internet of Things, allowing for detailed instrumentation and data collection. WSNs face challenges due to resource constraints, energy limitations, and harsh environmental conditions. They must operate for extended periods with minimal energy consumption, often turning off most components when not in use. The dense deployment of nodes requires efficient networking protocols to manage connectivity and interactions. Despite these challenges, WSNs offer significant opportunities in environmental monitoring, structural health monitoring, condition-based maintenance, and other applications. Environmental monitoring, for example, involves collecting readings over large volumes of space to study internal variations. WSNs can provide simultaneous measurements at multiple points, spanning elevation and radial directions, over prolonged periods. This data helps in understanding growth dynamics, water intake, and nutrient transport in ecosystems. Motion monitoring applications, such as condition-based maintenance, use WSNs to detect wear and fatigue in structures like machines, bridges, and buildings. By performing local processing and continuous data transmission, WSNs can improve plant performance and reduce costs. The technology behind WSNs includes microprocessors, power sources, and sensors. Microcontrollers operate on low power, and MEMS sensors can sense a wide range of physical phenomena efficiently. Microradios enable wireless communication, though energy consumption remains a significant challenge. WSNs are built using layered networking protocols that manage physical radio devices, link layers, and packet layers. Data dissemination and collection are achieved through flooding protocols and tree formation, with reliability enhanced by disruption-tolerant networking approaches. Power and bandwidth conservation are crucial, with techniques such as local data processing, aggregation, and compression employed to optimize energy usage. Privacy concerns arise in settings with multiple potential users, requiring careful management of data collection and dissemination. The future of WSNs promises smaller, more integrated devices that will become integral to manufacturing processes and environmental monitoring. This evolution will require new information technology architectures and programming languages to fully realize their potential.