This paper proposes a rapid trajectory optimization approach using artificial neural network metamodel for two application areas i.e. firstly for incorporating trajectory optimization at the conceptual design level and secondly for guidance with onboard reoptimization of the trajectory in near real time. Particle Swarm Optimization is employed for conceptual design optimization, whereas, Sequential Quadratic Programming is used for onboard trajectory optimization. We first describe our methods for analyzing vehicle design and then we incorporate those methods into optimization problem, the solution of which yields minimized launch weight. In addition to optimal vehicle configuration, this study also optimizes ascent trajectory in an integrated manner. In second application area, closed loop guidance scheme uses trajectory metamodel based on neural network for online near real time trajectory optimization. Dispersion analysis of open loop guidance and proposed closed loop guidance are conducted and shows that proposed scheme makes the system more robust. Trajectory metamodel using neural network shows promising results for both guidance and conceptual design optimization applications.
Today, smart solutions are gaining more importance with the communication technology in all areas of life by governments. Especially if the issue is concerned with the health of citizens, and since drinking water is the most important requirement of life, so the great care of governments is to confirm the validity of drinking water, usually by using specific equipment where the water quality is tested on all characteristics such as minerals, temperature, etc. This process takes more time to complete for the selected sample. In this paper, the design implementation and development of a system for monitoring the quality of drinking water using Internet of Things (IoT) technology is presented and explained. The proposed system consists of several sensors to measure different variables such as pH value, turbidity in water, dissolved oxygen and, temperature and humidity. Also, a microcontroller unit (MCU) is connected with these sensors and further processing is done on the personal computer (PC). The data obtained is sent to the cloud using to the point of interest by Wi-Fi Module, can be viewed online using the Internet of Thing (IoT) technology and ThinkSpeak IoT-based application for water quality monitoring. The uniqueness of our proposed paper are obtain high frequency water control system, high mobility, was implemented, manufactured and tested in one of the localities and low power.
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