Wireless integrated network sensors (WINS) are a new type of distributed network that provides access to sensors, controls, and processors embedded in equipment, facilities, and the environment. WINS combine microsensor technology with low-power signal processing, computation, and low-cost wireless networking in a compact system. Recent advances in integrated circuit technology have enabled the development of more capable and inexpensive sensors, radios, and processors, allowing mass production of sophisticated systems that link the physical world to digital data networks. WINS can be used in a wide range of applications, including medicine, security, factory automation, environmental monitoring, and condition-based maintenance. The compact geometry and low cost of WINS allow them to be embedded and distributed at a fraction of the cost of conventional wireline sensor and actuator systems. WINS opportunities depend on the development of a scalable, low-cost sensor-network architecture. Such applications require the delivery of sensor information to the user at a low bit rate through low-power transceivers. Continuous sensor signal processing enables the constant monitoring of events in an environment where short message packets would suffice. Future applications of distributed embedded processors and sensors will require vast numbers of devices. Conventional methods of sensor networking represent an impractical demand on cable installation and network bandwidth. Processing at the source would drastically reduce the financial, computational, and management burden on communication systems. The paper discusses the physical principles behind distributed sensors, detection and estimation theory, and communications constraints. It also explores the design principles for achieving reliable decisions with low energy consumption, including the use of energy thresholding, limited frequency analysis, and data fusion. The paper also discusses the WINS network architecture, which must support large numbers of sensors in a local area with short range and low average bit-rate communication. The network design must address the requirement of servicing dense sensor distributions, emphasizing recovery of environmental information. The paper also discusses the WINS node architectures, which include the development of a modular platform for evaluating more sophisticated networking and signal-processing algorithms. The paper concludes that the physical considerations are making it possible to pursue the innovative design of densely distributed sensor networks and the resulting advantages of layered and heterogeneous processing and networking architectures for related applications. The close intertwining of network processing is a central feature of systems connecting the physical and virtual worlds. Development platforms are now available that will increasingly allow a broader community to engage in fundamental research in networking and new applications, advancing developers and users alike toward truly pervasive computing.Wireless integrated network sensors (WINS) are a new type of distributed network that provides access to sensors, controls, and processors embedded in equipment, facilities, and the environment. WINS combine microsensor technology with low-power signal processing, computation, and low-cost wireless networking in a compact system. Recent advances in integrated circuit technology have enabled the development of more capable and inexpensive sensors, radios, and processors, allowing mass production of sophisticated systems that link the physical world to digital data networks. WINS can be used in a wide range of applications, including medicine, security, factory automation, environmental monitoring, and condition-based maintenance. The compact geometry and low cost of WINS allow them to be embedded and distributed at a fraction of the cost of conventional wireline sensor and actuator systems. WINS opportunities depend on the development of a scalable, low-cost sensor-network architecture. Such applications require the delivery of sensor information to the user at a low bit rate through low-power transceivers. Continuous sensor signal processing enables the constant monitoring of events in an environment where short message packets would suffice. Future applications of distributed embedded processors and sensors will require vast numbers of devices. Conventional methods of sensor networking represent an impractical demand on cable installation and network bandwidth. Processing at the source would drastically reduce the financial, computational, and management burden on communication systems. The paper discusses the physical principles behind distributed sensors, detection and estimation theory, and communications constraints. It also explores the design principles for achieving reliable decisions with low energy consumption, including the use of energy thresholding, limited frequency analysis, and data fusion. The paper also discusses the WINS network architecture, which must support large numbers of sensors in a local area with short range and low average bit-rate communication. The network design must address the requirement of servicing dense sensor distributions, emphasizing recovery of environmental information. The paper also discusses the WINS node architectures, which include the development of a modular platform for evaluating more sophisticated networking and signal-processing algorithms. The paper concludes that the physical considerations are making it possible to pursue the innovative design of densely distributed sensor networks and the resulting advantages of layered and heterogeneous processing and networking architectures for related applications. The close intertwining of network processing is a central feature of systems connecting the physical and virtual worlds. Development platforms are now available that will increasingly allow a broader community to engage in fundamental research in networking and new applications, advancing developers and users alike toward truly pervasive computing.