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The global pandemic situation has severely affected all countries. As aresult, almost all countries had to adjust to online technologies to continuetheir processes. In addition, Sri Lanka is yearly spending ten billion onelections. We have examined a proper way of minimizing the cost of hostingthese events online. To solve the existing problems and increase the timepotency and cost reduction we have used IoT and ML-based technologies.IoT-based data will identify, register, and be used to secure from fraud, whileML algorithms manipulate the election data and produce winning predictions,weather-based voters attendance, and election violence. All the data will besaved in cloud computing and a standard database to store and access the data.This study mainly focuses on four aspects of an E-voting system. The mostfrequent problems across the world in E-voting are the security, accuracy, andreliability of the systems. E-government systems must be secured againstvarious cyber-attacks and ensure that only authorized users can accessvaluable, and sometimes sensitive information. Being able to access a systemwithout passwords but using biometric details has been there for a while now,however, our proposed system has a different approach to taking thecredentials, processing, and combining the images, reformatting and producingthe output, and tracking. In addition, we ensure to enhance e-voting safety.While ML-based algorithms use different data sets and provide predictions inadvance.

Web and Mobile Platforms for Managing Elections based on IoT And Machine Learning Algorithms