Abstract
Companies that produce energy transmit it to any or all households via a power grid, which is a regulated power transmission hub that acts as a middleman. When a power grid fails, the whole area it serves is blacked out. To ensure smooth and effective functioning, a power grid monitoring system is required. Computer vision is among the most commonly utilized and active research applications in the world of video surveillance. Though a lot has been accomplished in the field of power grid surveillance, a more effective compression method is still required for large quantities of grid surveillance video data to be archived compactly and sent efficiently. Video compression has become increasingly essential with the advent of contemporary video processing algorithms. An algorithm’s efficacy in a power grid monitoring system depends on the rate at which video data is sent. A novel compression technique for video inputs from power grid monitoring equipment is described in this study. Due to a lack of redundancy in visual input, traditional techniques are unable to fulfill the current demand standards for modern technology. As a result, the volume of data that needs to be saved and handled in live time grows. Encoding frames and decreasing duplication in surveillance video using texture information similarity, the proposed technique overcomes the aforementioned problems by Robust Particle Swarm Optimization (RPSO) based run-length coding approach. Our solution surpasses other current and relevant existing algorithms based on experimental findings and assessments of different surveillance video sequences utilizing varied parameters. A massive collection of surveillance films was compressed at a 50% higher rate using the suggested approach than with existing methods.
Highlights
As discussed by Memos et al [1], the number of SwitchMode Power Supply is increasing, as are incentive-based switching activities at the end-user level
Some thresholds may be adjusted by the user in commercially available equipment for power quality (PQ) measurement at sample rates ranging from 10 kHz to 100 megahertz; raw data is captured when an event happens
As a challenging and essential topic, real-time video compression has sparked a lot of studies. is corpus of information has been included in the motion video standards to a large extent
Summary
As discussed by Memos et al [1], the number of SwitchMode Power Supply is increasing, as are incentive-based switching activities at the end-user level. A high-resolution time-resolution monitoring system will be required for future smart grids’ operational stability to properly examine the state of the electricity grid. When it comes to power grid measurement applications, kilohertz frequencies are used, but the degree of aggregation and the reporting rate is not the same. It is important to note that waveforms only change at the equipment’s contact state or load alterations in terms of distortions These operations are slow compared to the length of time. We have chosen to focus on the development of compression with no degradation techniques and performances for grid data at a lot of sampling to address these issues in the present contribution.
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