Development of Raspberry Pi Based Election Logistic Intelligent Robot

The electoral empire saddled with election process in Nigeria faces numerous logistical challenges which include the timely distribution of election materials, secure transportation of ballot boxes, and effective monitoring of voting stations. These challenges are exacerbated by factors such as inadequate infrastructure, security concerns, and the sheer scale of operations across diverse and most especially in remote regions. This paper proposes a solution to these challenges by developing an Election Logistics Intelligent Robot (ELIR) based on the Raspberry Pi platform. The ELIR is engineered to automate and optimize election logistics, thereby reducing human intervention and minimizing errors. The robot integrates sensors, cameras, and communication modules, enabling it to navigate complex environments autonomously while providing real-time data on election material status. Machine learning algorithms enhance its decision-making capabilities, ensuring efficient operation even in unpredictable situations. By leveraging this technology, the aim is to improve the reliability, speed, and security of Nigeria’s electoral logistics, ultimately contributing to a more transparent and efficient electoral process.