Optimization problem in remote areas had been a problem that could not be fully fixed and adjusted the field. This research focuses on optimizing distributed generator rescheduling in Sangihe Island, a remote region w...
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Monitoring natural water bodies like ponds is crucial due to environmental concerns. This study presents a new Pond Water Quality Monitoring System using Internet of Things (IoT) technology and six critical sensors: D...
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ISBN:
(纸本)9798350372977;9798350372984
Monitoring natural water bodies like ponds is crucial due to environmental concerns. This study presents a new Pond Water Quality Monitoring System using Internet of Things (IoT) technology and six critical sensors: Dissolved Oxygen (DO), Turbidity, Temperature, pH, Electro Conductivity (EC), and Salinity. Critical sensors monitor water quality in real-time. sensor data is sent to a cloud platform by microcontrollers via specific communication protocols. Clouds store, analyze, visualize, and interact with data. Stakeholders can monitor pond water quality via a website and Android apps. Graphs, charts, and maps depict temperature, pH, DO, turbidity, EC, and salinity changes in real-time. Users can take immediate action to avoid hazards when any parameter exceeds specified thresholds, thanks to a thorough warning mechanism. System data analysis yields advanced insights. Ecological health and the origins of pollution are shown by water quality data patterns, trends, and anomalies. Remote pump, aerator, and dosing device management help maintain ponds with accurate ***-based Pond Water Quality Monitoring System changes pond management. It uses IoT and sensor technologies to inform stakeholders, improve the preservation of the environment, protect aquatic ecosystems for future generations, and enable effective fish farming expansion by monitoring pond water and providing useful insights. The project develops an IoT-based pond water quality monitoring system for mobile and online apps.
This research paper presents the design and implementation of an automated hydroponic system capable of managing both closed and open setups in indoor and outdoor environments. The system integrates sensors and microc...
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Modern ieee 802.11 (Wi-Fi) networks extensively rely on multiple-input multiple-output (MIMO) to significantly improve throughput. To correctly beamform MIMO transmissions, the access point needs to frequently acquire...
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ISBN:
(纸本)9798350339864
Modern ieee 802.11 (Wi-Fi) networks extensively rely on multiple-input multiple-output (MIMO) to significantly improve throughput. To correctly beamform MIMO transmissions, the access point needs to frequently acquire a beamforming matrix (BM) from each connected station. However, the size of the matrix grows with the number of antennas and subcarriers, resulting in an increasing amount of airtime overhead and computational load at the station. Conventional approaches come with either excessive computational load or loss of beamforming precision. For this reason, we propose SplitBeam, a new framework where we train a split deep neural network (DNN) to directly output the BM given the channel state information (CSI) matrix as input. The DNN is designed with an additional "bottleneck" layer to "split" the original DNN into a head model and a tail model, respectively executed by the station and the access point. The head model generates a compressed representation of the BM, which is then used by the AP to produce the BM using the tail model. We formulate and solve a bottleneck optimization problem (BOP) to keep computation, airtime overhead, and bit error rate (BER) below application requirements. We perform extensive experimental CSI collection with off-the-shelf Wi-Fi devices in two distinct environments and compare the performance of SplitBeam with the standardieee 802.11 algorithm for BM feedback and the state-of-the-art DNN-based approach LB-SciFi. Our experimental results show that SplitBeam reduces the beamforming feedback size and computational complexity by respectively up to 81% and 84% while maintaining BER within about 10(-3) of existing approaches. We also implement the SplitBeam DNNs on FPGA hardware to estimate the end-to-end BM reporting delay, and show that the latter is less than 10 milliseconds in the most complex scenario, which is the target channel sounding frequency in realistic multiuser MIMO scenarios. To allow full reproducibility, we will r
Wireless Body Area Network (WBAN) is a vital application of IoT and EDGE technologies, which enable remote patient monitoring by transmitting real-time health data to a hospital server. WBAN faces congestion as a seve...
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The Internet of Things (IoT) is an emerging technology that gained significant attention in both academia as well as industry. It is a set of heterogeneous devices that are interconnected together for exchanging infor...
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Perfect power flow methods can be employed to choose which inverters will supply and determine their optimal real and reactive power settings based on financial goals. Utilizing advanced semidefinite relaxation make p...
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Power imbalance poses a significant challenge in decentralized microgrids because of the dynamic nature of distributed Energy Resources (DERs) and varying load conditions. Conventional voltage droop control methods, w...
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The hardware computing landscape is changing. What used to be distributedsystems can now be found on a chip with highly configurable, diverse, specialized and general purpose units. Such systems-on-a-Chip (SoC) are u...
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ISBN:
(纸本)9798350325454
The hardware computing landscape is changing. What used to be distributedsystems can now be found on a chip with highly configurable, diverse, specialized and general purpose units. Such systems-on-a-Chip (SoC) are used to control today's cyber-physical systems, being the building blocks of critical infrastructures. They are deployed in harsh environments and are connected to the cyberspace, which makes them exposed to both accidental faults and targeted cyberattacks. This is in addition to the changing fault landscape that continued technology scaling, emerging devices and novel application scenarios will bring. In this paper, we discuss how the very features-distributed, parallelized, reconfigurable, heterogeneous-that cause many of the imminent and emerging security and resilience challenges, also open avenues for their cure though SoC replication, diversity, rejuvenation, adaptation, and hybridization. We show how to leverage these techniques at different levels across the entire SoC hardware/software stack, calling for more research on the topic.
Multi-sensor data fusion technology has great potential to effectively solve the data compatibility problems inherent in smart devices. However, current methodologies lack high-performance delivery while neglecting ke...
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