IET Smart Cities最新文献

Biodiversity surveys are often required for development projects in cities that could affect protected species such as bats. Bats are important biodiversity indicators of the wider health of the environment and activity surveys of bat species are used to report on the performance of mitigation actions. Typically, sensors are used in the field to listen to the ultrasonic echolocation calls of bats or the audio data is recorded for post-processing to calculate the activity levels. Current methods rely on significant human input and therefore present an opportunity for continuous monitoring and in situ machine learning detection of bat calls in the field. Here, we show the results from a longitudinal study of 15 novel Internet connected bat sensors—Echo Boxes—in a large urban park. The study provided empirical evidence of how edge processing can reduce network traffic and storage demands by several orders of magnitude, making it possible to run continuous monitoring activities for many months including periods which traditionally would not be monitored. Our results demonstrate how the combination of artificial intelligence techniques and low-cost sensor networks can be used to create novel insights for ecologists and conservation decision-makers.

A dynamic digital twin is a feasible solution that can be employed to build real-time connectivity between virtual and physical objects. Industries like manufacturing, aerospace and healthcare utilise dynamic digital twins for simulation, monitoring and control purposes, but recently, this nascent technology has also attracted the interest of urban designers. Due to the novelty of the dynamic digital twin in urban design, this research study addresses the concept of digital twin technology and investigates its applicability in so-called smart city settings. Drawing on results from research interviews and examples from the Digital Twin project in Helsinki city, the research illustrates that solid data infrastructure forms the foundation for urban digital twins and the development of future smart city applications and services. Furthermore, data-enriched digital twins evidently accelerate smart city experimentations and strengthen both learning and knowledge-based decision-making. Digital twins have also proved that they offer an environment in which smart city practitioners can bridge multi-stakeholder urban design teams through one digital platform.

The trend towards cities and urbanisation, which increases the number of people living in urban areas, requires local authorities to provide services and natural resources more efficiently and effectively and develop some strategies for a sustainable environment. The more effective use of resources, growing awareness of sustainable environment, climate confidence and motivation to make cities more livable is a new concept called Smart City. In this study, the proposed system supports the garbage collection of the city government and works with low budget, low energy, and free radio frequencies. The Internet of Things (IoT) sensor node is assembled, and the network is set up based on the long range wide area network protocol to connect it to the sample garbage bin and collect data. Instant data collection by this network is carried out through the IoT and is designed based on the collected data. The goal is to build an ideal system for smart garbage collection in cities and support sustainability in cities by integrating with the city government's information systems. The data received from the sensor nodes and the efficiency of the system were demonstrated for local governments. The main outcome of this research is to develop a practical smart city application with minimal resources and support local governments in their daily work. Moreover, how a low power wide area network communication network with a frequency of 868 MHz works in Istanbul (Turkey) will be investigated further and which alternative to cellular networks is the most suitable for excellent communication in smart cities will be studied.

Smart city is one of the current trends of city evolvement. Smart city is a systematic project, which needs a holistic approach. As lots of pilot projects have been undertaken by cities, how to assess the ‘smartness’ of a city is of great importance. This study sums China's smart city standardisation and assessment practice, starting from the national policy evolvement, followed by the standardisation system, assessment and its key procedures and concludes with some possible future works regarding smart city standardisation and assessment.

The use of distributed energy resources (DERs) in a city contributes to the net zero CO₂ of a city. However, the spatially uneven distribution of power demand and surplus electricity causes congestion in the grid system, making wide-area operation difficult. The concept of local energy self-sufficiency via energy management, in which batteries or electric vehicles are charged using power generated by DERs and discharged to neighbouring consumers, is expected to be a way to avoid grid conjunction while maximizing the use of DERs. For efficient local energy self-sufficiency, it is necessary to identify where and when future power surpluses and shortages will occur within a city and optimize battery operation according to demand. Forecasts that focus only on representative points of a city may be less reproducible in diversity in the power demand transition for individual consumers in local parts of cities. Electricity smart meters that monitor power demand every 30 min from each consumer are expected to help predict the spatiotemporal distribution of power demand to achieve efficient local energy self-sufficiency. The significance of reflecting regional characteristics in forecasting spatiotemporal distribution of power demand is demonstrated using actual data obtained by smart meters installed in Japanese cities. The results suggest that the forecast approach, which considers the daily periodicity of power demand and weather conditions, obtains high prediction accuracy in predicting power demand in meshed local areas in the city and derives results precisely reproducing the spatiotemporal behaviours of power demand.

The deployment of domestic smart metering infrastructure in Great Britain provides the opportunity for identification of home appliances utilising non-intrusive load monitoring methods. Identifying the energy consumption of certain home appliances generates useful insights for the energy suppliers and for other bodies with a vested interest in energy consumption. Consequently, the domestic smart metering system, which is an integral part of the smart cities' infrastructure, can also be used for home appliance identification purposes taking into account the limitations of the system. In this article, a step-by-step description on accessing data directly from the domestic Smart Meter via an external Consumer Access Device is described, as well as an easy-to-implement method for identifying commonly used home appliances through their power consumption signals sampled at a rate similar to the rate available by the domestic smart metering system. The experimental results indicate that the combination of time domain with frequency domain features extracted either from the 1D/2D Discrete Fourier Transform or the Discrete Cosine Transform provides improved recognition performance compared to the case where the time domain or the frequency domain features are used separately.

Electric power grid infrastructure has revolutionized our world and changed the way of living. So has blockchain technology. The hierarchical electric power grid has been shifting from a centralized structure to a decentralized structure to achieve higher flexibility and stability, and blockchain technology has been widely adopted in the energy sector to deal with grid management, billing, metering, and so on, because of its nature of decentralization. Here, the aim is to provide a multi-dimensional review on the technological advances of the blockchain in smart grids. Its corresponding applications based on these advances, including company projects and use cases, are summarized. Furthermore, the security threat issues in smart grids, Ethereum Virtual Machine (i.e. the operating environment of consensus mechanisms), and smart contracts are analysed, with a brief conclusion to manifest the prior tasks in building secure blockchain-based infrastructures in smart grids. As such, the challenges and features of different protocols and their applicability in each use case are identified to provide an insightful guide for future research studies.