In both developed and developing countries, air pollution is increasing daily, compromising the air quality index and causing harm to everyone. Some of the reasons for this rapid increase in air pollution include the growing population, rising number of industries, rapid urbanization, and excessive use of fuel-consuming transportation. Hence, there is an ever-increasing need to monitor air quality using an energy-efficient, ubiquitous and connected manner. The system presented in this project is an advanced real time air quality reporting system supported with Internet Of things (IOT) architecture. The term Internet of Things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. Degrading air qualit has been a matter of concern nowadays and real time monitoring of air quality helps us to keep a check on it.Air Quality is the scale to measure how polluted the air is. Greater air pollution indicates more dangerous air is for human health. The model presented here uses a combination of the Arduino IDE software and hardware along with a Gas sensors - MQ135, temperature and humidity sensor which help in detecting gases like NO2, CO, Ammonia, and Sulphide. Live location tracking and Data updating will also be done with the help of GPS and IOT. Further, this research work monitor the Air Quality over an IOT analytics application BLYNK using internet connected with the hardware. It can also integrate the real time data into our mobile phone app. The circuit finally displays the PPM values as well as Air Quality level of gases on an Android application which fetches data from sensor through IoT. The current model is implemented successfully and can be deployed for real system implementations. Key Word: Air quality, Temperature, Humidity , Fire
Typically, renewable energy offers clean energy along with effective and optimal utilization on comparing other conventional sources of energy. On relating other renewable sources, solar photovoltaic (PV) based generation of power is accessible readily. This is employed widely for charging, lighting, and pumping of solar and so on. The issue associated with energy is minimized by using pollution-free renewable sources of energy without having emission and the maximum output power is attained using optimization process. For this purpose, this article presents a SEPIC based DC-to-DC converter design with the soft switching operation for the wide conversion operation of E-Automobiles. The solar PV source is given to boost converter with the use of Hierarchical Multi-Heuristic Chicken Swarm Optimization (HMH-CSO) based Maximum Power Point Tracking (MPPT) scheme. The converted source is given to SEPIC converter at which the Fuzzy Logic Controller (FLC) is employed. A SEPIC converter is a DC-to-DC converter that converts the fixed range of DC supply to the variable range of DC supply using duty ratio. The zero-voltage source (ZVS) soft switching operation of converter is provided. The converted output is inverted by means of three-phase inverter at which the generation of pulse width modulation (PWM) is made by means of FLC controller employed. The inverted output is given to the load (BLDC motor) by filtering using Low Pass Filter (LPF). Thus, an efficient generation of power is made and is given to the load of BLDC motor side. The performance analysis is made for traditional PID (Proportional-Integral-Derivative) controller and FLC controller and the outcomes attained for both controllers are compared to show the efficiency of proposed FLC controller. The performance is estimated in terms of Rise time, peak time, peak overshoot, settling time, delay time, output voltage, output current, and steady state error. The comparative analysis shows that proposed design using FLC controller offers better outcome than others.
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