Abstract
In this paper, we analyze and predict the temperature and humidity using IoT and linear regression algorithm in machine learning. In ancient days, people use to check the climate conditions by seeing clouds or through storm warnings or by using animals they have noticed the weather conditions for many purposes like harvesting and involves many household activities. To overcome this situation, weather forecasting was found. We collect the temperature and humidity data in various places for few days using Message Queuing Telemetry Transport (MQTT) protocol. So, we initialize the collected data for 5 days in Amazon Web services (AWS) cloud. This data is stored in AWS and by using Dynamo Database (DynamoDB) the stored data is created in the form of the table and it is exported to .csv file. Hence, the data is recorded. Now by using linear regression algorithm in machine learning, we predict the temperature and humidity data. People can therefore easily monitor the weather conditions without eagerly waiting for tomorrow. This makes more easy and comfortable way to the people so that they will be able to know the climatic conditions within a short period of time.
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Vamseekrishna, A., Nishitha, R., Kumar, T.A., Hanuman, K., Supriya, C.G. (2021). Prediction of Temperature and Humidity Using IoT and Machine Learning Algorithm. In: Bhattacharyya, S., Nayak, J., Prakash, K.B., Naik, B., Abraham, A. (eds) International Conference on Intelligent and Smart Computing in Data Analytics. Advances in Intelligent Systems and Computing, vol 1312. Springer, Singapore. https://doi.org/10.1007/978-981-33-6176-8_30
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DOI: https://doi.org/10.1007/978-981-33-6176-8_30
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