IPC분류정보
국가/구분 |
United States(US) Patent
등록
|
국제특허분류(IPC7판) |
|
출원번호 |
US-0188469
(2002-07-02)
|
발명자
/ 주소 |
- Lind, Michael A.
- Priddy, Kevin L.
- Morgan, Gary B.
- Griffin, Jeffrey W.
- Ridgway, Richard W.
- Stein, Steven L.
|
출원인 / 주소 |
- Battelle Memorial Institute
|
대리인 / 주소 |
Woodard, Emhardt, Moriarty McNett &
|
인용정보 |
피인용 횟수 :
76 인용 특허 :
133 |
초록
▼
An intelligent microsensor module (10, 100, 210, 300, 355, 410) is provided that can fuse data streams from a variety of sources and then locally determine the current state of the environment in which the intelligent microsensor is placed. The resultant state rather than raw data is communicated to
An intelligent microsensor module (10, 100, 210, 300, 355, 410) is provided that can fuse data streams from a variety of sources and then locally determine the current state of the environment in which the intelligent microsensor is placed. The resultant state rather than raw data is communicated to the outside world when the microsensor is queried. The intelligent microsensor module (10, 100, 210, 300, 355, 410) of the present invention can locally determine and execute an action to be taken based on the determined state of the environment. The module (10, 100, 210, 300, 355, 410) can be readily reconfigured for multiple applications.
대표청구항
▼
1. A modular general purpose sensor unit, comprising:a sensor array layer to receive and condition data from at least two different types of sensor; a general purpose intelligent processor and control layer to process at least said conditioned data and produce output data derived from said condition
1. A modular general purpose sensor unit, comprising:a sensor array layer to receive and condition data from at least two different types of sensor; a general purpose intelligent processor and control layer to process at least said conditioned data and produce output data derived from said conditioned data, said processor and control layer including a reprogrammable memory for storing application specific software to control the operation of said processor and control layer, said output data being at least partially different from said conditioned data; a power layer for providing power to said sensor array layer and said processor and control layer; wherein said sensor array layer, said processor and control layer, and said power layer are layered to form a sensor module. 2. The modular general purpose sensor unit of claim 1, further comprising a communications layer for transmitting and receiving information to and from said sensor module, said sensor module including said communications layer.3. The modular general purpose sensor unit of claim 2, wherein said sensor module includes a data port for receiving application specific software to be stored in said memory.4. The modular general purpose sensor unit of claim 2, wherein said memory can be programmed to perform a different application with application specific software received by said communications layer.5. The modular general purpose sensor unit of claim 2, wherein said communications layer receives other sensor output data from another sensor module.6. The modular general purpose sensor unit of claim 2, further comprising a removable passive layer including a plurality of types of sensors thereon, said removable passive layer being configured for a specific application, said removable passive layer further adapted to be placed in communication with said sensor array layer of said sensor module.7. The modular general purpose sensor unit of claim 6, wherein said smart sensor module can be reconfigured for a different application by replacing said removable passive layer with a second removable passive layer adapted to a second specific application and reprogramming said memory with second software adapted to said second specific application.8. The modular general purpose sensor unit of claim 6, wherein said passive layer includes microfluidics channels and further comprising a process control layer to control fluid flow through said microfluidics channels on said passive layer by non-contact actuation.9. The modular general purpose sensor unit of claim 6, wherein said output data is used by said sensor module to adjust a parameter being monitored.10. The modular general purpose sensor unit of claim 1, wherein said two different types of sensors are chosen from a group including sensors that respond to temperature, pressure, vibration, electric fields, magnetic fields, optical irradiation, particle radiation, thermal radiation, momentum, acceleration, shock, flow, viscosity, density, mass, shear strain, conductivity, impedance, sound, ultrasound, specific organic elements, inorganic chemical elements, inorganic chemical compounds, inorganic chemical complexes in liquid gas, inorganic chemical in solid phases, proteins, enzymes, antigens, antibodies, other DNA fragments, genes and olignonucleotides.11. The modular general purpose sensor unit of claim 10, wherein said two different types of sensors are included on a removable passive layer in communication with said sensor array layer of said unitary smart sensor module.12. A sensor communication network, comprising: a plurality of general purpose smart sensor devices, each comprising:a sensor array layer to receive and condition data from at least two different types of sensor; a general purpose intelligent processor and control layer to process at least said conditioned data and produce output data derived from said conditioned data, said processor and control layer including a reprogrammable memory for storing application specific software to control the operation of said processor and control layer, said output data being at least partially different from said conditioned data; a power layer for providing power to said sensor array layer and said processor and control layer; wherein said sensor array layer, said processor and control layer, and said power layer form a sensor module; a central station for receiving said data; and wherein said output data from each of said smart sensor devices is communicated to said central station. 13. The sensor communication network of claim 12, additionally including:a plurality of node controllers, each node controller interacting with a portion of said plurality of general purpose smart sensor devices; and at least one site node controller in communication with said plurality of node controllers and with said central station. 14. The sensor communication network of claim 13, wherein at least a portion of said smart sensor devices communicate with at least one of said node controllers using a communication system chosen from the group including: the BLUETOOTH protocol, active RF communications and passive RF communications.15. The sensor communication network of claim 13, wherein at least a portion of said node controllers communicate with said site node controller using a communication system chosen from the group including long range RF, cell phone, satellite link, land wire, fiber optics, IR links, internet links.16. A method, comprising:performing a first sensing application with a sensing device, the sensing device including a power source, a processor, a wireless communication device, a first layer to perform sensing with two or more sensors each of a different type, and a memory including first application programming corresponding to one or more features of the first layer; interchanging the first layer of the sensing device with a second layer, the second layer including at least one feature different from the one or more features of the first layer, the memory including second application programming corresponding to the at least one feature of the second layer; and performing a second sensing application with the sensing device after said interchanging, the second application being different than the first application. 17. The method of claim 16, wherein the power source, the processor, and the wireless communication device are each carried on a different one of a number of layered carriers coupled together to provided an integral sensing subassembly.18. The method of claim 16, which includes wirelessly communicating first information from the sensing device for the first sensing application and second information from the sensing device for the second sensing application.19. The method of claim 16, wherein the sensors are carried in a sensor layer and said providing includes reprogramming the memory before said performing the second sensing application.20. The method of claim 19, wherein the first layer is in the form of a first passive layer that cooperates with the sensor layer to provide a first sensing configuration and the second layer is in the form of a second passive layer that cooperates with the sensor layer to provide a second sensing configuration.21. The method of claim 16, which includes processing information from the sensors with a neural network.22. A method, comprising:providing a plurality of sensing device subassemblies each including a power source, a processor, a wireless communication device, and two or more sensors each of a different type; coupling a first outer layer to one of the subassemblies to provide a sensing device for a first application; coupling a second outer layer to another of the subassemblies to provide a sensing device for a second application different than the first application; and executing a first program with the sensing device for the first application and a second program with the sensing device for the second application, the first program and the second program being at least partially different in accordance with a difference between features of the first outer layer and the second outer layer. 23. The method of claim 22, wherein said first outer layer and said second outer layer are each passive.24. The method of claim 22, which includes performing an actuation with the sensing device.25. The method of claim 22, wherein the power source, the processor, the wireless communication device, and the sensors are each carried on a different one of a corresponding number of layered carriers coupled together for each of the subassemblies.26. The method of claim 22, wherein the first program includes an adaptive learning routine.27. The method of claim 22, wherein the first outer layer includes microfluidics channels and which includes controlling fluid flow through the microfluidics channels by noncontact actuation.28. A method, comprising:providing a self-powered, remote sensor module carrying at least two sensors each operable to sense a characteristic of a different type and a wireless communication device; processing signals from the sensors with a neural network provided by the sensor module; and transmitting information from the sensor module with the wireless communication device, the information being at least partially determined from said processing. 29. The method of claim 28, wherein the sensor module includes a processor defining the neural network.30. The method of claim 28, wherein the sensor module comprises a first layer including a power source, a second layer including the wireless communication device, a third layer including the processor, and a fourth layer including the sensors.31. The method of claim 28, wherein the sensor module is one of a plurality of the sensor modules in wireless communication with a node.32. The method of claim 28, which includes locating an object or person carrying the sensor module.33. A method, comprising:providing a self-powered, remote sensor module carrying at least two sensors each operable to detect a characteristic of a different type; carrying the sensor module with one or more of a mobile person and a mobile object; processing signals from each of the sensors with an adaptive learning routine executed by the sensor module; and providing location information for the one or more of the mobile person and the mobile object at least partially based on said processing. 34. The method of claim 33, wherein the adaptive learning routine includes an algorithm based on at least one of the group consisting of: a self-organization feature map, adaptive resonance theory, a feed forward neural network, a recurrent neural network, and Hopfield and bi-directional associative memory learning.35. The method of claim 33, wherein the sensor module includes a processor defining a neural network that executes the adaptive learning routine.36. The method of claim 33, wherein the sensor module comprises a first layer including a power source, a second layer including a wireless communication device, a third layer including a processor, and a fourth layer including the sensors.37. The method of claim 36, wherein said providing includes wirelessly transmitting the location information with the wireless communication device.38. The method of claim 33, wherein the sensor module is carried with the mobile object and the mobile object is in the form of a package.39. The method of claim 33, wherein the sensor module is carried with the person and the sensor module detects one or more medical parameters of the person.40. A self-powered, sensor module, comprising:means for providing the sensor module in a number of layers coupled together to provide an integrated sensing unit with at least an outer one of the layers being interchangeable; means for sensing at least two different characteristics and providing corresponding sensor signals, said sensing means being coupled to said outer one of the layers; means for processing said sensor signals with an adaptive learning routine; and means for wirelessly communicating information from said processing means to a receiving device.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.