By Chia-Pang Chen, Cheng-Long Chuang, Joe-Air Jiang (auth.), Subhas Chandra Mukhopadhyay, Krishanthi P. Jayasundera, Anton Fuchs (eds.)
The booklet offers the hot developments within the quarter of sensors and sensing expertise, particularly in environmental tracking, structural health and wellbeing tracking, dielectric, magnetic, electrochemical, ultrasonic, microfluidic, circulation, floor acoustic wave, gasoline, cloud computing and bio-medical.
This booklet might be helpful to a number of readers, particularly, grasp and PhD measure scholars, researchers, practitioners, engaged on sensors and sensing expertise. The ebook will provide a chance of a devoted and a deep technique so that it will enhance their wisdom during this particular field.
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Additional info for Advancement in Sensing Technology: New Developments and Practical Applications
The data delivery rate is defined by the following formula: θ= Dr Dt × 100%, (1) where Dr is the actual number of sets of data that the gateway received, and Dt is the number of sets of data that the gateway should receive. To verify the robustness of the proposed gateway, a large number of sensor nodes were evenly deployed in an indoor room. The size of the experimental site was about 6 m × 1 m. 1 Indoor Experiments To test whether the proposed gateway could still work properly after connecting to a large number of sensor nodes, a series of experiments with different numbers of sensor nodes were conducted, ranging from 20 to 40.
If no sensor nodes respond to the ACK signal, this means that the deployment of this round fails and the gateway will reboot to redeploy the sensor network again. If the deployment stage is successful, the gateway will calculate the data delivery rate of the successful round. If the data delivery rate is lower than a predetermined threshold, then the gateway will broadcast a redeployment command to redeploy the whole sensor network. On the other hand, if the data delivery rate is acceptable, then the gateway will save the routing results and send these results to the back-end server so that administrators can monitor the routing status of the network.
Towards Low-Power Operation Careful power analysis of the ﬁrst prototype board revealed that longer term (months) deployment could be achieved by utilizing advanced power management techniques, by eliminating the (re)conﬁguration phase and by lowering the static power consumption associated with SRAM FPGAs. This recognition led to a second prototype, “AEPod”, where power management has been separated into an independent low-power microcontroller and the SRAM FPGA has been replaced with a ﬂash FPGA .
Advancement in Sensing Technology: New Developments and Practical Applications by Chia-Pang Chen, Cheng-Long Chuang, Joe-Air Jiang (auth.), Subhas Chandra Mukhopadhyay, Krishanthi P. Jayasundera, Anton Fuchs (eds.)