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The video surveillance is critical system to track the people at the various places and to track and monitor the nuciencess bound to be happened. On the other side several studies have proved and showed the hit and miss nature of human intervention to spot change in a surrounding environment which increasing the designer challenges for the development of video surveillance system with the help of embedded processor. The designer faces a greater challenge to apply the principle of embedded systems and develop the system smart features with low power and cost for the required applications of VSS. System requirement specification (SRS), Hardware design document (HDD), Software design document and test procedure has been arrived and developed to achieve VSS system. Blackfin processor has high end video engines and is more suitable for development of video surveillance system (VSS). The VSS is designed and developed using ADSP BF533 Ez-kit lite board. Peripheral like parallel peripheral interface (PPI) is used to interface between camera and processor. Also, it is used for interfacing processor and TV. The master-slave communication is established between two Blackfin processors through SPORT to transfer the captured frame from camera to display on TV. Power management is also implemented to save the power of the system.

The ubiquitous presence of microplastics as contaminants in the ecosystem has become a matter of environmental concern gaining considerable attention in the research community as well as public arena. Lack of efficient collection and improper management of plastic have resulted in the enormous amounts of plastic wastes landing into the marine systems with oceans being the ultimate sink. Due to non-biodegradability, these plastics break down into smaller fragments over a period of time leading to consumption by aquatic species, threatening marine life. In the recent years, a wide range of food products has also been contaminated with microplastics directly affecting human health. This review focuses on the separation and identification technologies for extraction and detection of microplastics in food and marine ecosystems. Efficient technologies like floatation, membrane separation, chemical treatment, enzymatic treatment, and other miscellaneous techniques have been discussed considering their merits and demerits. Additionally, identification technologies like optical detection, scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, thermo-analytical methods, and hyperspectral imaging have been emphasized for the detection of microplastic particles. The emerging techniques like enzymatic digestion combined with hyperspectral imaging could be a possible way for obtaining higher separation efficiency and characterization with minimal harm to food sample. This article narrows the gap for choosing a standard separation technology for microplastic detection in food matrices keeping in mind the composition, particle size, shape, data visualization techniques and cost.

Energy reduction of functional units (FUs) is a very important concern for high-end superscalar processors, not only because FUs consume a significant portion of processor energy, but also because they are one of the most important hotspots in the processor. In addition, the high sensitivity of leakage on temperature and process variation result in very high variation in the FU power consumption in different processor dies. Such high process variation reduces the parametric yield of processors. Consequently, reducing the FU power consumption and its variation is an important problem. However, existing FU power reduction techniques assumes all the FUs are similar, and do not consider the sensitivity of leakage on temperature. Consequently, they are not very effective in reducing the variation of FU power consumption. The advent of extremely small, yet accurate leakage sensors allow us to develop leakage-aware microarchitectural techniques to reduce both the power consumption and its variation among processor dies. Our leakage-aware operation-to-FU binding mechanism (LAOFBM) and leakage-aware power gating (LA-PG) mechanisms reduce the mean and standard deviation of the total arithmetic logic unit (ALU) power consumption of the ALPHA 21364 by 34% and 59%, respectively. At the processor level, this translates to a 13% reduction in the total processor energy consumption, with a 24°C reduction in the maximum ALU temperature.