The fieldserver is an Internet based observation robot that can provide an outdoor solution for monitoring environmental parameters in real-time. The data from its sensors can be collected to a central server infrastructure and published on the Internet. The information from the sensor network will contribute to monitoring and modeling on various environmental issues in Asia, including agriculture, food, pollution, disaster, climate change etc. An initiative called Sensor Asia is developing an infrastructure called Sensor Service Grid (SSG), which integrates fieldservers and Web GIS to realize easy and low cost installation and operation of ubiquitous field sensor networks.
The Real Estate prediction model is a web-based Machine Learning project which uses the machine learning algorithm to determine the price of the house in the future. This project targets the people who are in search of a place for living with a suitable price and a living standard. To get better and accurate results we have used multiple algorithms and compared them. The findings have indicated that the use of various algorithms can drastically impact the accuracy of the prediction. And, having a poor dataset negatively impacts the prediction. Different factors like interest rates, housing inventory, absorption rates, rental to capitals and many more impact the price of the real estate. So, we would like to make a model which predicts the price precisely keeping these factors in mind.
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