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Global Precision Viticulture Strategic Business Report

Dublin, April 06, 2023 (GLOBE NEWSWIRE) The "Precision Viticulture: Global Strategic Business Report" report has been added to . ....

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Humanitarian Initiatives (SIGHT) | IEEE Microwave Theory and ...

The IMARC 2014 which was held in Bangalore marked an onset off MTT-S getting involved as a society for international humanitarian initiatives. The 6 SIGHT . ....

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Global Industrial Internet of Things Market Report 2023-2028: Combining Ai With Digital Twins, Cloud Robotics, and Teleoperation to Drive Substantial Market Opportunities for Systems Integration

/PRNewswire/ The "Global Industrial Internet of Things Market by IIoT Technologies, Solutions and Services 2023-2028" report has been added to. ....

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"Complete Targets Coverage in Energy Harvesting Internet of Things With" by Rui Yang, Changlin Yang et al.

This article considers deriving set covers or the set of active nodes that are responsible for monitoring all targets in an Internet of Things (IoT) network. A key distinction to prior works is that this article considers sensor nodes aided by backscatter communications, which allow them to communicate with negligible energy cost using ambient radio frequency (RF) signals. The article contains three main novelties. First, it presents a mixed integer linear program (MILP) that can be used to compute the global optimal solution. Second, it also outlines a centralized greedy scheduling (CGS) algorithm that selects nodes based on their energy and the number of covered targets. Third, it presents a distributed greedy scheduling (DGS) algorithm that selects nodes according to their energy level. The simulation results show that equipping nodes with ambient backscattering capability increases the ratio of complete targets coverage by more than 100% as compared to existing techniques. ....

Duty Cyle , Energy Management , Scheduling Algorithms , Wireless Sensor Networks ,

"Maximizing Sensing and Computation Rate in Ad-Hoc Energy Harvesting Io" by Hang Yu and Kwan Wu Chin

This paper considers collection and processing of data by solar-powered servers operating in an Internet of Things (IoT) network. Specifically, these servers aim to cooperatively maximize the amount of data collected from devices and computed over multiple time slots. To achieve this aim, they must consider computation deadline, time-varying energy arrivals at sensor devices and other servers. To this end, this paper outlines a mixed integer linear program (MILP), which can be used to optimize the sensing time of sensor devices, offloading decision of each server, and the number of virtual machines (VMs) assigned to each device. Further, this paper proposes a multi-agent co-operative Q-learning approach coupled with the Hungarian algorithm to assign VMs to devices. It allows servers to learn when to share their energy and VMs with neighbor servers using only non-causal energy and channel gain information. The simulation results show that the amount of processed data by co-operative Q-l ....

Ad Hoc Networks , Data Collection , Edge Computing , Nternet Of Things , Q Learning , Renewable Energy , Task Analysis , Wireless Communication , Wireless Sensor Networks ,