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Chronic Obstructive Pulmonary Disease (COPD) is a set of lung diseases in which the airways constrict, making it difficult to expel air from the lungs. COPD is caused by longterm lung damage from breathing a potential hazard, mainly frequently cigarette smoking, as well as smoke from other sources and air pollution. Also, some rural areas where people are exposed to dust, flames, and chemicals can contribute to the onset of COPD. COPD is supposed to after 40 years. Some major problems getting short of breath, having cough, wheezing, also produced more sputum, respiration rate abnormal, sometimes getting restless. In Bangladesh, day by day patients with COPD are increasing. So, in this case, need to analyze the symptoms of COPD and finds why it is increasing day by day. In this research, we have taken 101 COPD patients data from the hospital which are in two classes. In the medical sector, work for COPD is rare in Bangladesh. Our goal is to find the most appropriate machine learning approach for COPD prediction which is both computationally efficient and accurate. Decision Tree and Logistic Regression outperformed all other machine learning algorithms, according to the findings in our study.

A simple and low power standalone photovoltaic (PV) water pumping system with conventional centrifugal pump is presented here. The system uses a DC-DC boost converter which extract the maximum power from the solar array and a Sine Pulse Width Modulation (SPWM) technique based Voltage Source Inverter (VSI) for DC-AC conversion. The DC link voltage is controlled by varying pump speed to match the available solar power to pump power. The proposed control scheme requires no additional current and speed sensor. The simulation is performed in MATLAB/SIMULINK under different radiation condition. The simulation results show that the pump can run under low radiation and can fill up a 1000 liter tank within the average sun hours.

This paper introduces a mobile, web and swarm robotics based solution system that is useful for taking necessary actions to solve problems like rapid changes in climate, sustainable human settlement planning, and sudden climate related hazards. This system is consist of robotics mobile application and web. The system will create a distributed sensor nodes using low cost wireless sensors. As a result system will develop connected network for smart sensing. Swarm robots will be used to communicate with each other and do the mapping of an area, sub bots will send signal to mother bot and after completing the task they will return to mother bot. anyone can see the real time data of mapping in web portal. To protect against natural disaster system will help to detect flood before it hit's an area. After practical studies and simulating data the efficiency of the system is established. The end result shows the feasibility, reliability, galactic impact of the system. This paper shows more possible research scope in natural disaster monitoring.