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Farrukh Hafeez
Universiti Teknologi Malaysia

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Distant temperature and humidity monitoring: prediction and measurement Farrukh Hafeez; Usman Ullah Sheikh; Attaullah Khidrani; Muhammad Akram Bhayo; Saleh Masoud Abdallah Altbawi; Touqeer Ahmed Jumani
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1405-1413

Abstract

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Co-Authors Attaullah Khidrani Muhammad Akram Bhayo Saleh Masoud Abdallah Altbawi Touqeer Ahmed Jumani Usman Ullah Sheikh