Blockchain turns both currencies and commodities into a digital form without relying on middleman which allows one person to trade with another include trading the renewable energy. Blockchain technology as a secure and low-cost platform to track the billions of eventual transactions in a distributed energy economy has attracted the attention of experts in various fields of science. The current form of centralized energy trading system is still suffering from security concerns, quality of service, and to name a few. A decentralized energy system using blockchain technology allows the parties to create a trading energy transaction via microgrid. The blockchain technology offers the promise of an immutable, single source of truth from multiple sources without a third-party involvement. In this paper, we describe, explore and analyze the prominent implementation of blockchain technology in the energy sector. Furthermore, we analyze the security issues and highlight the performance of several attacks that might be occurred in the proposed system.
The national education department's inventory record is unique because the goods are in schools under service, not in the office. Inventory complexity has increased due to the procurement of different schedules and reports, not only for internal but also for other institutions concerned. A structured and accessible inventory from anywhere is the right choice for the effectiveness and efficiency of this work. This research aims to design a website-based information system for goods inventory in the National Education Office (DISDIKNAS). The software development method used in this study is the Rational Unified Process. The study results obtained a web-based application that can help DISDIKNAS inventory goods in a structured and accessible anywhere
This research produces an application that can send automatic notifications in the form of a chat on the Telegram platform when a weapon object is detected on CCTV. This application was created utilizing computer vision technology and artificial intelligence, in particular YOLOv7. As demonstrated by the mAP@0.5 value of 0.837 after 50 epochs of training, this application can detect weapon objects such as people, pistols, and knives with a reasonable degree of accuracy. This application is also linked to the telepot library, which enables it to send chats on the Telegram platform. These applications can aid in enhancing security and safety in a variety of environments and have numerous practical applications in fields such as public safety, law enforcement, and others. However, there are still deficiencies in this study that can be addressed in future research, such as the small number of training epochs and the size of the dataset.
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