This review critically approaches the literature on smart cities while describing the significance of more value‐based rationality and more reflexive practice for constructing smart cities, rethinking how human experiences are approached to improve it to be more balanced and engaging. This transition establishes a sense of place in the city necessary to enhance people's attitudes and overall well‐being. As the vision of smart cities promotes them as more liveable cities while focusing on achieving more efficient services, the review clarifies the need to improve the ability of smart cities to produce more engaging experiences to achieve long‐term sustainable development, planning and governance as part of their green transition. The authors promote innovative approaches to realising agendas of citizen engagement and sustainability by clarifying the potential of interdisciplinary cooperation among art, place and technology. This will help redefine progress in city development from merely enhancing basic functions to improving the human experience.
Fixed cycle traffic lights primarily regulate road traffic, in which traffic light control systems are for specific lanes or crossings in urban areas. Also, not being appropriately installed can prolong the congestion delay and unnecessarily long wait times for crossing intersections, which can cause emergency vehicles to become stuck at intersections. Adaptive signal timing management technique that is more computationally viable than current fixed cycle signal control systems and can improve network‐wide traffic operations by reducing traffic delay and energy consumption. Even though specific adaptive control systems exist, there is no mechanism to communicate with emergency vehicles, which is crucial for smart cities. Motivated by this problem, a novel framework, Emergency Vehicle Adaptive Traffic Light (EVATL), is proposed for smart cities where an adaptive mode of operation for traffic lights is employed with emergency vehicle communication, improving their functioning and reducing overall congestion delay. EVATL detects emergency vehicle location using GPS with the Internet of Things(IoT), which integrates with traffic signals and works adaptively according to vehicle density at the traffic signal using YOLOv8. So, the primary goal of the proposed EVATL is to prioritise an emergency vehicle while simultaneously integrating adaptive traffic signals for smart cities. A GUI is developed for evaluating the proposed model by creating different scenarios for an adaptive traffic light and emergency vehicle communication. While analysing the simulation results of the proposed model EVATL, a clear improvement can be seen in the wait time of vehicles at a traffic light with the timely detection of an emergency vehicle at a set distance.
Adaptive signal timing management technique that is more computationally viable than current fixed cycle signal control systems and can improve network‐wide traffic operations by reducing traffic delay and energy consumption. Even though specific adaptive control systems exist, there is no mechanism to communicate with emergency vehicles, which is crucial for smart cities. Motivated by this problem, a novel framework, Emergency Vehicle Adaptive Traffic Light (EVATL), is proposed for smart cities where an adaptive mode of operation for traffic lights is employed with emergency vehicle communication, improving their functioning and reducing overall congestion delay. EVATL detects emergency vehicle location using GPS with the Internet of Things(IoT), which integrates with traffic signals and works adaptively according to vehicle density at the traffic signal using YOLOv8. So, the primary goal of the proposed EVATL is to prioritise an emergency vehicle while simultaneously integrating adaptive traffic signals for smart cities.image
The emergence of smart cities is set to transform transportation systems by leveraging real‐time traffic data streams to monitor urban dynamics. This complements traditional microscopic simulation methods, offering a detailed digital portrayal of real‐time traffic conditions. A framework for near‐real‐time city‐scale traffic demand estimation and calibration is proposed. By utilising Internet of Things (IoT) sensors on select roads, the framework generates microscopic simulations in congested networks. The proposed calibration method builds upon the standard bi‐level optimization formulation. It presents a significant computational advantage over available methods by (i) formulating the optimization problem as a bounded variable quadratic programming, (ii) acquiring sequential optimization technique by splitting computations into short time frames while considering the dependency of the demand in successive time frames, (iii) performing parallel simulations for dynamic traffic assignment in corresponding time frames using the open source tool Simulation of Urban MObility (SUMO), and (iv) feeding traffic count data of each time frame as a stream to the model. The approach accommodates high‐dimensional real‐time applications without extensive prior traffic demand knowledge. Validation in synthetic networks and Tartu City case study showcases scalability, accuracy, and computational efficiency.
This paper presents a computationally efficient framework for near‐real‐time high‐dimensional dynamic demand estimation and microscopic traffic simulation in city‐scale congested networks. The actual traffic count data is fed to the proposed method as an hourly aggregated stream collected by IoT sensors, and the system continues to function as long as it receives the data without bounding the performance time. The case study of the city of Tartu demonstrates the technique's application to a large‐scale network of 2780 nodes and 6700 links, generating 24 hourly microscopic simulations of 197,000 vehicles with high accuracy and under a tight computational budget.image
This article promotes the role and importance of art in the research and making of smart cities. To elucidate the potential of using relational artworks for a more vibrant interaction in the city as well as various visuals in knowledge production and/or implications of overlooking them, a case study of Milton Keynes is presented in the article. Visual comparisons and analysis contributed to making the argument clearer by reflecting on the situation on the ground. Qualitative methods have been used for data collection and analysis, which included interviews, document analysis and on‐field observations. The findings were presented under three main sections: Innovation in knowledge production, vocabulary and design, and art in Milton Keynes and Milton Keynes in art. The themes are used to clearly discuss the need for innovative methods in knowledge production and cities making while explaining the benefits of integrating art with science. By reflecting on the benefits of accommodating the need for effective communication, higher engagement and fulfilling experience in research and design of cities, the powers of visual and relational art are unpacked throughout the article. Thus, the role of art is introduced to be beyond that of decoration to help facilitate cities development and production.
The COVID‐19 pandemic has increased the need for social distancing and improved sanitation to prevent the spread of infectious diseases. In the waste management sector, protecting the safety and health of waste collection labourer has become a priority. In Japan, the labour shortage problem and ageing demography have intensified the need for contactless waste collection technology. This study responds to this need by reviewing the global practice of smart waste collection technologies and observing the situation of the Japanese waste collection system through participant observation. Based on the identified trends and status, the authors developed a contactless waste collection system and tested it on an actual working site. The demonstration showed that the system could safely lift a 700 L waste container containing 212 kg of waste to the collection truck without human contact. Labourers can be reduced from 2 to 1 person to operate the collection truck. This study also discovered the smart bin's potential to motivate the reduction of packaging waste consumption.
This study observed the current waste collection practice in Japan. An automated contactless waste collection system was developed in this study. The demonstration revealed that the system can empty a 700L waste container safely without human contact.image
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