Electronic voting (e-voting) systems are gaining increasing attention as a means to modernize electoral processes, enhance transparency, and boost voters’ participation. In recent years, significant developments have occurred in the study of e-voting and blockchain technology systems, hence reshaping many electoral systems globally. For example, real-world implementations of blockchain-based e-voting have been explored in various countries, such as Estonia and Switzerland, which demonstrates the potential of blockchain to enhance the security and transparency of elections. Thus, in this paper, we present a survey of the latest trends in the development of e-voting systems, focusing on the integration of blockchain technology as a promising solution to address various concerns in e-voting, including security, transparency, auditability, and voting integrity. This survey is important because existing survey articles do not cover the latest advancements in blockchain technology for e-voting, particularly as it relates to architecture, global trends, and current concerns in the developmental process. Thus, we address this gap by providing an encompassing overview of architectures, developments, concerns, and solutions in e-voting systems based on the use of blockchain technology. Specifically, a concise summary of the information necessary for implementing blockchain-based e-voting solutions is provided. Furthermore, we discuss recent advances in blockchain systems, which aim to enhance scalability and performance in large-scale voting scenarios. We also highlight the fact that the implementation of blockchain-based e-voting systems faces challenges, including cybersecurity risks, resource intensity, and the need for robust infrastructure, which must be addressed to ensure the scalability and reliability of these systems. This survey also points to the ongoing development in the field, highlighting future research directions such as improving the efficiency of blockchain algorithms and integrating advanced cryptographic techniques to further enhance security and trust in e-voting systems. Hence, by analyzing the current state of e-voting systems and blockchain technology, insights have been provided into the opportunities and challenges in the field with opportunities for future research and development efforts aimed at creating more secure, transparent, and inclusive electoral processes.

Structural Health Monitoring (SHM) is a process of detecting damages to engineering structures. The goal of SHM is to improve both the safety and reliability of infrastructures such as buildings, bridges, and highways. Several efforts have been made to develop improved SHM systems. However, most of these studies only considered vibration as a monitoring parameter without incorporating expert systems based on fuzzy inference. In this work, an expert system was incorporated into SHM for monitoring residential buildings based on building temperature and vibration measurements. The developed system used a Wireless Sensor Network (WSN) with a 2.4 GHz Radio Frequency (RF) band. Results of the system performance evaluation indicated a decrease in reliability from 99% to 50% within a decade of its deployment. In terms of energy conservation, results showed that the system was able to save 30% of energy, thereby increasing its lifetime. The fuzzy expert SHM system is able to detect building conditions with a good level of reliability, energy conservation capability and high accuracy of 94.4% and 100% as the least and best performance, respectively. Hence, direct integration of this system into building structures could aid early detection of building impairment.

The conventional voting scheme employs paper-based ballot to verify votes. This voting scheme is insecure due to the attributed shortcomings including ballot stuffing, ballot snatching and voter's impersonation. In this paper, we present the design and development of secure e-voting to ensure a free, fair and credible election where the preference of electorate counts. This proposed system solves the authentication, integrity and confidentiality security issues of e-voting in kiosk and poll site evoting scenarios using unimodal fingerprint biometrics and Advanced Encryption Standard based Wavelet based Crypto-watermarking Approach. The developed system solves: The possibility of blundering voter's authentication, integrity and confidentiality of vote stored in the server. The results after qualitative evaluation of the system with antiwatermarking detectors revealed that the developed secure e-voting system could serve as a platform for the delivery of credible e-election in developing countries with significant digital divides.

This paper focuses on the development of maize plant datasets for the purposes of recognizing maize plants and weed species, as well as the precise automated application of herbicides to the weeds. The dataset includes 36,374 images captured with a high-resolution digital camera during the weed survey and 500 images annotated with the Labelmg suite. Images of the eighteen farmland locations in North Central Nigeria, containing the maize plants and their associated weeds were captured using a high-resolution camera in each location. This dataset will serve as a benchmark for computer vision and machine learning tasks in the intelligent maize and weed recognition research.