IET Smart Cities最新文献

The transportation system needs innovative schemes and applications to facilitate mobility in the cities that is user-friendly, easy, enjoyable and convenient according to citizens' constraints. In this study, the authors propose a decentralised architecture-based game-theoretic model for a community-based transportation system. This scheme, which involves multi-transportation forms, allows the user to be an active prosumer who can travel in the city using public and private forms and also make decisions about the trip cost. The authors propose a decentralised game-theoretic transportation algorithm to manage passenger needs, public bus interests, car ride-sharing and bicycle constraints. The simulations prove the effectiveness of the proposed scheme. The effectiveness of the decentralised game-theoretic transportation model appears more clearly when compared with the multi-mode double dynamic approach in [1], as it gives much better optimisation results.

In this study, a method is proposed for ultra high frequency radio frequency identification (UHF RFID)-based book positioning and counting developed for smart libraries. In the experimental setup created, RFID tags placed in books were automatically detected using three RFID antennas. Using received signal strength indicator information from each antenna for each book, the locations of the books are determined. In addition, classification was made by using machine learning approaches for the study. For this purpose, the best result for sequence determination in the classification study using ensemble trees, K nearest neighbours (KNN), and support vector machine algorithms was obtained with the ensemble subspace KNN algorithm with 94.1%. The best result for cabinet detection was obtained in the study using the ensemble subspace KNN algorithm and a 78.5% accuracy rate was achieved. The best result for rack detection was obtained with the ensemble subspace KNN algorithm with 95.4%. The study is thought to be useful in the automatic determination of the row, cabinet, and rack of books in smart libraries.

Coffee is an important economic crop and one of the most popular beverages worldwide. The rise of speciality coffees has changed people's standards regarding coffee quality. However, green coffee beans are often mixed with impurities and unpleasant beans. Therefore, this study aimed to solve the problem of time-consuming and labour-intensive manual selection of coffee beans for speciality coffee products. The second objective of the authors’ study was to develop an automatic coffee bean picking system. They first used image processing and data augmentation technologies to deal with the data. They then used deep learning of the convolutional neural network to analyse the image information. Finally, they applied the training model to connect an IP camera for recognition. They successfully divided good and bad beans. The false-positive rate was 0.1007, and the overall coffee bean recognition rate was 93%.

This study presents a review of smart light-emitting diode (LED) lighting systems applied to smart buildings. The study is focused on drivers, protocols, technologies, communication networks and applications. An extended overview of the methodologies used for LED lighting control in smart buildings is addressed. The study also presents an integrated architecture able to achieve the necessary services and control methodologies for intelligent building energy management system for LED lightings systems in smart buildings.

Electricity theft is a notable aspect of power distribution utilities due to advance in the non-technical loss. It results imbalance between power supply and demand. It consequence overload of the distribution network and extraneous tariff invoke on legally connected consumers. The advance metering infrastructure is useful for an energy audit of every distribution transformer due to a communication facility. However, direct hooking on distribution overhead line or tapping from underground cables remains an interminable issue which has to be rigorously decimated. The objective of this study is to present real-time electricity theft detection and prevention scheme (ETDPS) with the available infrastructure in the field. The proposed ETDPS is based on programmable logic control; it identifies the pilferage locations and estimates the power stolen by illegal consumers. The prototype is tested in the laboratory and the results demonstrate that the ETDPS works satisfactorily under diversified operating conditions. The proposed scheme is implemented as a part of their Smart City Pilot Project by Maharashtra State Electricity Distribution Company Limited, Nagpur (India) and the performance demonstrates its feasibility.

For nearly three decades, becoming smart has been claimed to be a solution to urban problems. This claim is justified, but not unconditionally. This article aims to contribute to the development of a human-centric smart city agenda, which in effect means the application of social and ecological principles, in conjunction with appropriate technology. In order to achieve this goal, smart city literature has been critically assessed for its contribution to the agenda. Five narratives that represent different ways of framing the role of (digital) technologies in solving urban problems have been summarised and commented on. It was concluded that the use of (digital) technology should be preceded by examining the complexity of social and ecological problems of contemporary cities. This vision resulted in a re-conceptualisation of the smart city concept into a city that aligns the use of technology with its human-centric agenda. Kate Raworth' concept of a doughnut economy has proven useful in designing such an agenda. This concept is based on the simultaneous application of principles related to social and environmental sustainability, resulting in an agenda of 39 ‘city actions’ for cities that intent to be humane by choice and smart by default.