DATA SECURITY, MODELING AND VISUALIZATION OF DATA FROM IOT DEVICES
Journal Title: Scientific Journal of Astana IT University - Year 2022, Vol 10, Issue 10
Abstract
The article describes the IoT infrastructure, the hardware of the IoT system, considers the issue of security of the chosen LoRa data transmission technology. Data was received from sensors for gas, temperature and humidity, atmospheric pressure, as well as the location of the end device. At the same time, the standardized security features of the selected LoRa technology for transmitting data from sensors to the server were investigated. The article deals with LoRa bi-directional secure communication line, the security function requires devices/end devices to be configured through the LoRa gateway. Security research is devoted to the development of a security mechanism to increase its resilience. The payload was formed with a hash of the last bytes, and the entire payload was encrypted with AES for integrity and confidentiality. A method for assessing and visualizing atmospheric air pollution is given on the example of the city of Almaty, Kazakhstan. The process of numerical modeling of the study of emissions of harmful substances into the atmosphere is based on a mathematical model formed by the system of Navier-Stokes equations, consisting of the continuity equation, as well as the equations of motion and the k-epsilon turbulence model. To test the numerical methods for processing mixing and chemical reactions, a test problem was chosen – a jet in a transverse flow. Three-dimensional numerical simulation has been implemented. The use of the Internet of Things (IoT) and the acquisition of big data made it possible to simultaneously observe the concentrations of several pollutants in the atmosphere, calculate this concentration and analyze the state of the surface air layer. Modeling allows forecasting the possible concentration of pollutants in certain areas at certain times of the year.
Authors and Affiliations
B. Imankulova, S. Alpar, S. Amanzholova
Keywords
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- EP ID EP712454
- DOI 10.37943/ACWT2121
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