An AI-Powered VVPAT Counter for Elections in India
Prasath Murugesan, Shamshu Dharwez Saganvali
TL;DR
This paper presents an AI-powered VVPAT counter that automates the verification process, significantly improving efficiency and scalability for election audits in India.
Contribution
It introduces a novel image processing and machine learning-based system to automate VVPAT verification, addressing scalability issues in election auditing.
Findings
Automated system reduces verification time.
Improves accuracy of VVPAT counting.
Enables full-scale election audits.
Abstract
The Election Commission of India has introduced Voter Verified Paper Audit Trail since 2019. This mechanism has increased voter confidence at the time of casting the votes. However, physical verification of the VVPATs against the party level counts from the EVMs is done only in 5 (randomly selected) machines per constituency. The time required to conduct physical verification becomes a bottleneck in scaling this activity for 100% of machines in all constituencies. We proposed an automated counter powered by image processing and machine learning algorithms to speed up the process and address this issue.
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Taxonomy
TopicsInternet Traffic Analysis and Secure E-voting · Vehicle License Plate Recognition
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings · Pointwise Convolution · Residual Connection · Batch Normalization · *Communicated@Fast*How Do I Communicate to Expedia? · Depthwise Convolution · Depthwise Separable Convolution · Inverted Residual Block · 1x1 Convolution · Average Pooling