EAI Endorsed Transactions on Smart Cities

Vehicle counting application utilizing background subtraction method with large-scale camera data

2024-04-18T08:07:17+00:00

In modern society, people are increasingly using cameras at home, in shops, and on the streets. Traffic systems have also invested in building more surveillance camera systems. The data collected by cameras contains valuable information for traffic regulation and recording traffic violations. The challenge is how to effectively use this data. In this article, we will discuss the use of real-time data from surveillance cameras on some roads in Da Nang City for vehicle counting using background subtraction methods. Additionally, we also tested the detection of red light violations to contribute to the development of a smart traffic system. So, the use of background subtraction in analyzing real-time data from surveillance cameras can greatly improve traffic management

Evaluation of Frameworks for MLOps and Microservices

2023-11-13T09:29:20+00:00

Information Technology involves solutions for many kinds of industries and organizations, offering conditions for solving problems of different types and complexities. Artificial Intelligence, and more specifically applications that considers Machine Learning (ML) and Software Technology are part of these solutions for solving problems, including solutions for solving problems that involve smart cities approach. In order to present frameworks that deal with the operationalization of Machine Learning and Software technology, this article is based on the study and evaluation of frameworks that involve Machine Learning Operations (MLOps) and microservices. Specifically, three frameworks that integrate ML algorithms with microservices are evaluated based on a bibliographical review in scientific journals of relevance to the area. From an exploratory analysis of these frameworks, it was possible to highlight their main objectives, their benefits, and their ability to offer solutions that favor the large-scale use of Machine Learning algorithms in problem solving. The main results are highlighted in the article through a qualitative analysis that considers six evaluation criteria, such as: capacity for sharing resources, scope of use by users, and use in a cloud environment. The results achieved are satisfactory since the work allows, through a qualitative view of the evaluated frameworks, a perspective of how the integration of MLOps and microservices has been carried out, its benefits and possible results achieved through this integration.

A Contemporary Approach to Designing and Implementing Electronic Voting Systems (EVS)

2024-03-14T12:32:39+00:00

This study delves into the potential of Electronic Voting Systems (EVS) in Ghana, to enhance transparent and trustworthy electoral processes. We presented a comprehensive framework highlighting trust, diaspora engagement, and human factors in voting. The study proposes a robust EVS framework for Ghana, emphasizing trust and accountability, preventing electoral fraud, and encouraging African governments to invest in IT and collaborate with experts in e-government and e-voting systems. We commence with a detailed systems analysis, identifying specific electoral challenges in Ghana. An artifact is designed and developed, and the artifact's effectiveness is demonstrated through Design Science Research Methodology (DSRM). We evaluated its alignment with the desired solution for Ghana's electoral issues. We emphasize the potential of EVS to address electoral challenges in Ghana and underscore the importance of proactive government policies, IT investments, and collaboration with IT experts. User acceptance testing achieved a remarkable 98% approval rate, showcasing the feasibility of implementing EVS at the national level. This research underlines the pivotal role of EVS in Ghana and advocates for visionary government policies and investments in IT. These measures can modernize electoral systems, align them with international standards, and promote democratic progress while preventing electoral fraud in Ghana and other African nations to avoid condemnation and punishment of unconstitutional transfers of power that are being challenged by meticulously planned takeovers.

Development of a Smart Waste Management System with Automatic Bin Lid Control for Smart City Environment

2024-04-18T11:34:46+00:00

As cities worldwide transform into smart, interconnected urban environments, the management of municipal waste emerges as a pressing challenge. This paper, titled "Development of a Smart Waste Management System with Automatic Bin Lid Control," offers a sophisticated solution that integrates seamlessly within the concept of smart cities. This system harnesses the power of the Internet of Things (IoT) to optimize waste collection and enhance urban cleanliness. The primary aim of this project is to create a smart waste management system that extends beyond traditional waste bins. It introduces a network of intelligent waste containers equipped with automatic lid control mechanisms that operate based on real-time waste level data. When approaching these bins, the lid control mechanism automatically opens the bin only if the waste level is not full, thereby facilitating convenient waste disposal. In the context of smart cities, this innovative approach presents several advantages. It optimizes waste collection efficiency by prioritizing bins in need of immediate attention and ensures that waste containers are not prematurely emptied, reducing unnecessary waste disposal trips. Moreover, the system enables city authorities to gain insights into waste level trends, fostering data-driven and proactive waste management strategies for a cleaner, more sustainable urban environment.