IoT-Enhanced Weather Monitoring System: Affordable Hardware Solution for Real-Time Data Collection, Storage, And Predictive Analysis (Published)
An IoT-based weather monitoring system that collects and stores weather data allowing easier access and recording is what this project entails. It is also incorporated with the ability to predict future weather data based on previous recordings. Keeping track of weather conditions is one of the most concentrated areas in our current society. Weather monitoring systems are built to collect these data from a wide range of areas. And there exist satellite systems which do similar work over a wider range of area. The goal of this project is to develop an inexpensive weather monitoring system that can gather these same data over a given area over time. The system is made of hardware built with ESP8266 (NodeMCU) and a website. The hardware device and the server transfer data using the industry-standard HTTP connection protocol. There exist various sensors like temperature sensors, humidity sensors, rain sensors and pressure sensor which are suitable for the full functioning of the system. These sensors collect and transmit data to a server via a Wi-Fi module to be stored and can be accessed on the webpage. These data are then analysed and used in predicting future data.
Keywords: IoT, Real-time data collection, Weather Monitoring, low-cost solution., predictive analysis
Predicting Student University Admission Using Logistic Regression (Published)
The primary purpose is to discuss the prediction of student admission to university based on numerous factors and using logistic regression. Many prospective students apply for Master’s programs. The admission decision depends on criteria within the particular college or degree program. The independent variables in this study will be measured statistically to predict graduate school admission. Exploration and data analysis, if successful, would allow predictive models to allow better prioritization of the applicants screening process to Master’s degree programme which in turn provides the admission to the right candidates.
Keywords: Logistic regression, college admission, data analytics, predictive analysis