Dataset Information

DPU-ALDOSKI dataset of Monitoring and Controlling distributed far distances energy consumed system based on Internet of Things.

ABSTRACT: This article presents the created dataset obtained from implementation of a proposed distributed energy management system based on the Internet of Things (IoT). The proposed approach was implemented and evaluated at two distinct institutions, namely Duhok and Shekhan, which are geographically distant from each other. The proposed system comprises two primary phases, namely Monitoring and Controlling, which are implemented using ESP32 microcontrollers. The power usage indicators, namely Voltage, current, and Frequency, have been subjected to meticulous monitoring and regulation. Three principal methodologies are employed for each institution, namely: comprehensive monitoring of all metrics for the entire institution, comprehensive monitoring of all metrics for the uncontrolled laboratory, and monitoring and regulation of all metrics for the controlled laboratory. The technology in question continuously collects data, leading to the creation of a substantial energy management database. The data collection process involved the utilization of server-side protocols, namely Message Query Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP).

SUBMITTER: M Sadeeq MA

PROVIDER: S-EPMC10415710 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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DPU-ALDOSKI dataset of Monitoring and Controlling distributed far distances energy consumed system based on Internet of Things.

M Sadeeq Mohammed A MA Zeebaree Subhi R M SRM

Data in brief 20230728

This article presents the created dataset obtained from implementation of a proposed distributed energy management system based on the Internet of Things (IoT). The proposed approach was implemented and evaluated at two distinct institutions, namely Duhok and Shekhan, which are geographically distant from each other. The proposed system comprises two primary phases, namely Monitoring and Controlling, which are implemented using ESP32 microcontrollers. The power usage indicators, namely Voltage, ...[more]

PMID: 37577740

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Project description:The oil and gas industries (OGI) are the primary global energy source, with pipelines as vital components for OGI transportation. However, pipeline leaks pose significant risks, including fires, injuries, environmental harm, and property damage. Therefore, maintaining an effective pipeline maintenance system is critical for ensuring a safe and sustainable energy supply. The Internet of Things (IoT) has emerged as a cutting-edge technology for efficient OGI pipeline leak detection. However, deploying IoT in OGI monitoring faces significant challenges due to hazardous environments and limited communication infrastructure. Energy efficiency and fault tolerance, typical IoT concerns, gain heightened importance in the OGI context. In OGI monitoring, IoT devices are linearly deployed with no alternative communication mechanism available along OGI pipelines. Thus, the absence of both communication routes can disrupt crucial data transmission. Therefore, ensuring energy-efficient and fault-tolerant communication for OGI data is paramount. Critical data needs to reach the control center on time for faster actions to avoid loss. Low latency communication for critical data is another challenge of the OGI monitoring environment. Moreover, IoT devices gather a plethora of OGI parameter data including redundant values that hold no relevance for transmission to the control center. Thus, optimizing data transmission is essential to conserve energy in OGI monitoring. This article presents the Priority-Based, Energy-Efficient, and Optimal Data Routing Protocol (PO-IMRP) to tackle these challenges. The energy model and congestion control mechanism optimize data packets for an energy-efficient and congestion-free network. In PO-IMRP, nodes are aware of their energy status and communicate node's depletion status timely for network robustness. Priority-based routing selects low-latency routes for critical data to avoid OGI losses. Comparative analysis against linear LEACH highlights PO-IMRP's superior performance in terms of total packet transmission by completing fewer rounds with more packet's transmissions, attributed to the packet optimization technique implemented at each hop, which helps mitigate network congestion. MATLAB simulations affirm the effectiveness of the protocol in terms of energy efficiency, fault-tolerance, and low latency communication.

Dataset Information

DPU-ALDOSKI dataset of Monitoring and Controlling distributed far distances energy consumed system based on Internet of Things.

Publications

DPU-ALDOSKI dataset of Monitoring and Controlling distributed far distances energy consumed system based on Internet of Things.

Similar Datasets

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