A survey on algorithms for intelligent computing and smart city applications

Abstract

With the rapid development of human society, the urbanization of the world's population is also progressing rapidly. Urbanization has brought many challenges and problems to the development of cities. For example, the urban population is under excessive pressure, various natural resources and energy are increasingly scarce, and environmental pollution is increasing, etc. However, the original urban model has to be changed to enable people to live in greener and more sustainable cities, thus providing them with a more convenient and comfortable living environment. The new urban framework, the smart city, provides excellent opportunities to meet these challenges, while solving urban problems at the same time. At this stage, many countries are actively responding to calls for smart city development plans. This paper investigates the current stage of the smart city. First, it introduces the background of smart city development and gives a brief definition of the concept of the smart city. Second, it describes the framework of a smart city in accordance with the given definition. Finally, various intelligent algorithms to make cities smarter, along with specific examples, are discussed and analyzed.

An Entropy-View Secure Multi-Party Computation Protocol Based on Semi-honest Model

“…Due to the abusive use of a lot of data, in order to make the private data use pricing problem, Shen et al [38] used information entropy to quantitatively analyze the private data, so that the use of private data can be effectively and reasonably distributed, and discussed issues such as price measurement of private data. In the field of smart cities and smart applications [39,40], intelligent computing is still needed for intelligence and cyber security to solve the problem of security vulnerabilities in products and to ensure security. Additionally, Wang et al [32] explored the fairness of secure twoparty computation, and we extended it to secure multi-party computation to study security and fairness issues.…”

A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars

“…Recently, artificial neural networks have been widely used and achieved outstanding performances in fields such as computer vision [12], edge computing [13,14,15,16,17,18], anomaly detection [19,20,21], data mining [22,23,24,25], algorithm optimization [26,27,28,29], medical diagnosis [30,31], and climate prediction [32], etc. This has attracted widespread attention from researchers in the field of weather forecasting, and they began to apply these networks to radar echo extrapolation.…”

A blockchain‐ and artificial intelligence‐enabled smart IoT framework for sustainable city

“…15 Although blockchain technology is comparatively modern, it has developed dramatically and applied in many areas, including business, healthcare, and IoT. 16,17 After gaining significant progress in earlier versions, Blockchain 5.0 is devised to serve the next-generation's applications demands by formalizing, regulating, standardizing the digital lifelines. Hence, it is becoming extremely valuable in today's world to have Blockchain 5.0.…”