RFID (radio-frequency identification) is the use of a wireless non-contact system that uses radio-frequencyelectromagnetic fields to transfer datafrom a tag attached to an object, for the purposes of automatic identification and tracking [38]. The basic technologies for RFID have been around for a long time. Its root can be traced back to an espionage device designed in 1945 by Leon Theremin of the Soviet Union,whichretransmittedincidentradiowaves modulatedwith audioinformation. After decades of development, RFID systems have gain more and more attention from both the research community and the industry.
标签： infrastructure RFID as an
上传时间： 2020-06-08
上传用户：shancjb
Internet of Things (IoT) [26] is a new networking paradigm for cyber-physical systems that allow physical objects to collect and exchange data. In the IoT, physical objects and cyber-agents can be sensed and controlled remotely across existing network infrastructure, which enables the integration between the physical world and computer-based systems and therefore extends the Internet into the real world. IoT can find numerous applications in smart housing, environmental monitoring, medical and health care systems, agriculture, transportation, etc. Because of its significant application potential, IoT has attracted a lot of attention from both academic research and industrial development.
标签： Technologies Internet Things RFID for of
上传时间： 2020-06-08
上传用户：shancjb
Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.
标签： Embedded_Deep_Learning Algorithms
上传时间： 2020-06-10
上传用户：shancjb
