The voting system is a set of rules that determine how people’s intentions may be manifest and how decisions can be achieved. Normally, vote papers are placed in the voting box and then will be sorted and calculated manually. But the problem is the use of manpower in calculating the vote manually may lead to error in the counting of votes and it takes a long time to complete the calculation process. For this purpose, an electronic voting machine (EVM) was introduced, where in this work it replace the conventional voting method in which the vote card will be calculated automatically. This paper focusing on implementation of embedded system which will help in the election process, where the Arduino UNO uses as a controller. This system uses a simple counting system based on the detection of black mark on the vote card using infrared (IR) sensor. Then, LCD 16x2 will display the number of votes for the respective candidate and the servo motor will activate to sort the valid and invalid vote card into 2 compartments in the voting box.
Abstract.Friction is known to affect the performance of motion control system, especially in terms of its accuracy. Therefore, a number of techniques or methods have been explored and implemented to alleviate the effects of friction. In this project, the Artificial Intelligent (AI) approach is used to model the friction which will be then used to compensate the friction. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is chosen among several other AI methods because of its reliability and capabilities of solving complex computation. ANFIS is a hybrid AI-paradigm that combines the best features of neural network and fuzzy logic. This AI method (ANFIS) is effective for nonlinear system identification and compensation and thus, being used in this project.
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