Selected article for: "analysis system and drug administration"

Author: Hassan, A. B. M. K.; Ahmed, K. F.
Title: Design and analysis of an off-grid PV plant for higher utilization efficiency in the field of pharmaceutical industry considering global pandemic state
  • Cord-id: 8fdpcs6w
  • Document date: 2021_1_1
  • ID: 8fdpcs6w
    Snippet: According to the concern of WHO the less association of people in an office may restrict the likelihood of spreading this COVID-19 infection. On the other hand, the pharmaceutical companies are working hard to maintain uninterrupted production of vaccine and medicines. This paper focuses on the main layer which is the power system management and its utilization through automation and controlling remotely. In the design process the FDA (Food and Drug Administration) proposed structure and green e
    Document: According to the concern of WHO the less association of people in an office may restrict the likelihood of spreading this COVID-19 infection. On the other hand, the pharmaceutical companies are working hard to maintain uninterrupted production of vaccine and medicines. This paper focuses on the main layer which is the power system management and its utilization through automation and controlling remotely. In the design process the FDA (Food and Drug Administration) proposed structure and green energy solution is maintained. Solar energy utilization efficiency is increased using the data logging system and machine learning algorithms from archived data. A SCADA operated Off-Grid Solar PV Automation System has been proposed to increase the utilization efficiency. To predict solar power availability over time and perform efficient energy trafficking, the automation system will analyze previous data and perform situational awareness operations for uninterrupted solar power generation. A comprehensive analysis of the proposed automation system for pharmaceuticals industry applications has also been presented in this paper. The continuous monitoring system for this Off-Grid Solar PV power generating unit preserves multiple data entries, which increases with time and subjected to energy trafficking. And this energy trafficking based on machine learning increases the overall solar energy utilization efficiency from 64% to 99.92%. © 2021 AIUB Office of Research and Publication. All rights reserved.

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