IoT Enabled Smart Traffic System for Public and Emergency Mobility in Smart City

Nagarjuna, Gampa; Shashidhar, R; Puneeth, S B; Arunakumari, B. N.

doi:10.1109/i-smac49090.2020.9243489

Cited by 5 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The system proposed in [6,7] uses an ESP328 Wi-Fi module and a IR sensor network for traffic management. The Wi-Fi module is used to update the status of the vehicle count.…”

Section: Introductionmentioning

confidence: 99%

IoT based Dynamic Road Traffic Management System

Bhavana¹,

Likhitha²,

Manoj³

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Traffic due to automobiles is a major problem in many urban places in India as well as in other countries. Malfunctioning of the traffic lights and various other dysfunctionalities has led to traffic congestion which hurts the economy, environment, and overall quality of life. Hence it is very important to manage the traffic congestion problem effectively. In this paper, a prototype is proposed for a traffic management system using IR sensors, Arduino, serial to the parallel shift register, and LED displays. The density of the traffic is measured by placing the IR sensors at the 4 lane junction after a certain distance. The data collected from sensors is used to dynamically change the sequence of green lights as well as to dynamically change the green light delays. The proposed road traffic management system is implemented in the proteus software. For high traffic zone, a higher green light delay is given whereas for low density zone, the duration of the green light delay is reduced. The system is also designed in such a way as to give preference to the lanes which have no vehicles/very few vehicles by providing the least green light delays.

show abstract

“…The system proposed in [6,7] uses an ESP328 Wi-Fi module and a IR sensor network for traffic management. The Wi-Fi module is used to update the status of the vehicle count.…”

Section: Introductionmentioning

confidence: 99%

IoT based Dynamic Road Traffic Management System

Bhavana¹,

Likhitha²,

Manoj³

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…Smart Transportation and Mobility: Smart transportation systems utilize data and technology to enhance mobility, reduce congestion, and minimize environmental impact. This includes intelligent traffic management, electric vehicle charging networks, and even autonomous vehicles that promise safer and more efficient transportation [30,31].…”

mentioning

confidence: 99%

Optimal Water Management Strategies: Paving the Way for Sustainability in Smart Cities

Bouramdane

2023

Smart Cities

View full text Add to dashboard Cite

Global urbanization and increasing water demand make efficient water resource management crucial. This study employs Multi-Criteria Decision Making (MCDM) to evaluate smart city water management strategies. We use representative criteria, employ objective judgment, assign weights through the Analytic Hierarchy Process (AHP), and score strategies based on meeting these criteria. We find that the “Effectiveness and Risk Management” criterion carries the highest weight (15.28%), underscoring its pivotal role in strategy evaluation and robustness. Medium-weight criteria include “Resource Efficiency, Equity, and Social Considerations” (10.44%), “Integration with Existing Systems, Technological Feasibility, and Ease of Implementation” (10.10%), and “Environmental Impact” (9.84%) for ecological mitigation. “Community Engagement and Public Acceptance” (9.79%) recognizes involvement, while “Scalability and Adaptability” (9.35%) addresses changing conditions. “Return on Investment” (9.07%) and “Regulatory and Policy Alignment” (8.8%) balance financial and governance concerns. Two low-weight criteria, “Data Reliability” (8.78%) and “Long-Term Sustainability” (8.55%), stress data accuracy and sustainability. Highly weighted strategies like “Smart Metering and Monitoring, Demand Management, Behavior Change” and “Smart Irrigation Systems” are particularly effective in improving water management in smart cities. However, medium-weighted (e.g., “Educational Campaigns and Public Awareness”, “Policy and Regulation”, “Rainwater Harvesting”, “Offshore Floating Photovoltaic Systems”, “Collaboration and Partnerships”, “Graywater Recycling and Reuse”, and “Distributed Water Infrastructure”) and low-weighted (e.g., “Water Desalination”) strategies also contribute and can be combined with higher-ranked ones to create customized water management approaches for each smart city’s unique context. This research is significant because it addresses urban water resource management complexity, offers a multi-criteria approach to enhance traditional single-focused methods, evaluates water strategies in smart cities comprehensively, and provides a criteria-weight-based resource allocation framework for sustainable decisions, boosting smart city resilience. Note that results may vary based on specific smart city needs and constraints. Future studies could explore factors like climate change on water management in smart cities and consider alternative MCDM methods like TOPSIS or ELECTRE for strategy evaluation.

show abstract