Iot based Fire and Gas monitoring System

In infrastructure and industrial plants the rapid growth is creating environmental issues like pollution, climate change and malfunctioning. It has a great consequence for the requirement of an operationally adaptable, efficient, cheap and smart monitoring systems. For this purpose we come up with idea to use these kind of technology i.e the Internet of Things (IoT) in form of a solution. In this paper, we suggest wireless data gathering frameworks that enable each detector node to track the changes in the behavioural pattern of gases and to identify their role in gas leakage problem, whilst at the same time trying to minimize power consumption. In the proposed device, the temperature detector (DHT 11) the gas detector (MQ2,MQ7 and MQ135) and also humidity sensors are used to determine the environment and the undesirable gas within the manufacturing plant, gauged details can be connected to the web. In addition, our research findings demonstrated substantial energy efficiency and high-precision data analysis relative to conventional protection device strategies. For monitoring the fluctuation of parameters like air pollution levels from their normal levels in this case the sensing devices are connected to the embedded computing system.

Sector Rasterization Method for Images on a Video Device With Mechanical Scanning

The goal of this work was to create a method for sectoral rasterization for images on video devices with mechanical scanning that can be used for advertising purposes. Preparing an image for display on a machine with a mechanical sector scan requires the creation of software for transferring a classic rectangular raster to a sector raster. When implementing software for an embedded computing system of mechanical image scanning for advertising purposes, the task was to reproduce a raster image using concentrically located circles, which are divided into sectors. The ambiguity of the transition from a square to a sectorial raster lies in the variable area of the sectors as they move away from the center of the image. According to this fact, there are several sectors for each of the pixels near the central zone of the image, and several pixels for one sector to the periphery of the image. There is not possible to increase the resolution of a sector image due to hardware limitations, so a new method of sector rasterization for an image on a mechanically scanned video device was developed. The developed method combines algorithms that make it possible to transform a raster image into a sectorial raster using linear interpolation depending on the distance of the sector from the center of the image. Attention was also paid to assessing the time of the next complete revolution when starting the mechanical scanning system, which made it possible to reduce the time for obtaining a stable image from the moment the device was turned on. So, as the result of the research, the method of sectorial image rasterization was developed, as well as the algorithms that allow converting a raster image into a sectorial image were developed. Вased on the developed algorithms, the software product for an embedded image reproduction system and the software product for real-time video transmission over Wi-Fi communication with the conversion of a rectangular raster into a sector raster were created. By combining algorithms for converting a square raster to a sector one, the quality of image reproduction on a mechanically scanned video device was improved.

Survey of Engineering Models for Systems Biology

In recent years, the field of systems biology has emerged from a confluence of an increase both in molecular biotechnology and in computing storage and power. As a discipline, systems biology shares many characteristics with engineering. However, before the benefits of engineering-based modeling formalisms and analysis tools can be applied to systems biology, the engineering discipline(s) most related to systems biology must be identified. In this paper, we identify the cell as an embedded computing system and, as such, demonstrate that systems biology shares many aspects in common with computer systems engineering, electrical engineering, and chemical engineering. This realization solidifies the grounds for using modeling formalisms from these engineering subdisciplines to be applied to biological systems. While we document several examples where this is already happening, our goal is that identifying the cell as an embedded computing system would motivate and facilitate further discovery through more widespread use of the modeling formalisms described here.