Designing Data Communication Security System on LoRA Network Using PRESENT Algorithm

Cyber security in smart cities: A review of deep learning-based applications and case studies

The concept of "smart cities" The Internet of Things (IoT) is a multi-layered framework that allows cities to employ urban networks to enhance economic performance, generate innovative technological solutions, and more. Smart Cities are the result of a new age in information technology and smart economy growth, based on Internet mesh networks, communication networks, transmission networks, wireless networks, and other end-to-end sensor networks. The Internet of Things (IoT) is at the heart of it. The Internet of Things incorporates sensors into common things and links them through particular protocols for sharing data and communications over the Internet. Smart detection leads, location, monitoring, and administration are all provided by this modular architecture. A smart city of excellence must overcome three main factors: instrumented, linked, and intelligent, with the help of IoT technology. At this point of IoT development, smart cities can only arise through the interconnectedness of all of these smart elements. The goal of this essay is to learn how the Internet and sensors may assist in the development of smart cities.
 The study's main goal is to figure out how the Internet of Things, or IoT, is being used in smart cities. We also want to establish the necessity for IoT systems in these smart cities, as well as the issues that they may pose to individuals and society, via the research.
 Review secondary research papers, reviews, dissertations, and online documents from the EBSCO, Scopus, and Emerald databases to analyse and comprehend the usage of IoT in smart cities and the possible problems that its implementation may provide in order to accomplish the following goals.
 Municipal requirements are getting more complicated, necessitating the adoption of new technology like the Internet of Things to ensure that all of these cities' duties are completed. Although more cities are becoming smart via the usage of IoT in a number of businesses, the study shows that this IoT system is also creating worries about the security of citizens' data.

Internet of Things (IoT) "The smart city concept has become a dream that big cities in Indonesia want to achieve, basically the smart city concept focuses on developing the human element using technology. IoT opens up many opportunities for new services by connecting the physical world and the virtual world to various electronic devices. IoT aims to leverage cutting-edge technology to support sustainable services for governments and their citizens. Systematic Literature Review (SLR) is one method in conducting an overview of previous interrelated researchers. The purpose of the literature study in this research is to understand trending research topics, methods, and architecture in the development of smart cities with IoT. In this study, various interesting information was found in various research journals regarding the role of IoT in building a smart city that has a role to serve smart city infrastructure, identify and analyze trends, develop smart cities and become innovations for IoT. Based on the research, there are things that need to be done to improve the study to focus more on the role of IoT that can be more utilized. IoT is also one of the technologies that are widely used in several countries in the development of IoT in the future. IoT in smart cities will become an inseparable technology because humans will increasingly depend on IoT in their daily lives

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

Internet of Things (IoT) and Big Data have played a significant role in the development and sustainability of Smart Cities. They are the backbones of Smart Cities' efforts to connect human resources, social capital, and ICT infrastructure to address public challenges, achieve sustainable development and improve people's standard of life. It helps Smart Cities improve public services, such as water management, healthcare, education, security issues, transportation, energy usage, and other community to achieve a better life. Big Data helps to analyze, store and back-ups a massive amount of data generated in smart cities in seconds day by day. For this matter, different analytical tools are employed, such as data analytics, machine learning, statistics, and data mining. Even though there are many benefits offered to smart cities; the Smart Cities encounters challenges that need to be addressed. Many of these challenges focus on security and privacy, infrastructures and operational and handling massive data. This paper describes the overview of IoT, Big Data, and Smart Cities. The Applications of IoT and Smart Cities were also discussed; the features of Smart Cities and Big Data; Different challenges of IoT, Big Data, and Smart Cities are described. Also, the proposed research work has presented the relationship between IoT and Big Data to Smart Cities; the role of IoT and Big Data in smart cities was identified; finally, the future directions for IoT and Big Data regarding Smart Cities are discussed.

Smart cities have expanded rapidly with the introduction of Internet of Things (IoT) devices and edge computing techniques. Such technologies have transformed how cities function through the ability to deliver smart services and analyze data in real time. But that advancement also adds to the demanding issues about privacy and data security. In smart city environments, privacy-preserving is essential to protect sensitive data collected from different channels against leakage, abuse and unauthorized access. This work is a review of data security and privacy-preserving models made for edge computing and smart cities. It examines the advantages and disadvantages of existing machine learning, blockchain, cryptography, hybrid architectures of optimizing resources, scalability and efficiency. The review discusses open challenges, including interoperability, resource constraints and governance issues, as well as future research directions such as quantum-secure security, federated learning and AI-based adaptive models. The concepts aim to help researchers and policymakers establish strong, durable smart city infrastructures.

Big data and artificial intelligence based early risk warning system of fire hazard for smart cities

Smart City and IoT

LoRa has emerged as one of the promising long-range and low-power wireless communication technologies for Internet of Things (IoT). With the massive deployment of LoRa networks, the ability to perform Firmware Update Over-The-Air (FUOTA) is becoming a necessity for unattended LoRa devices. LoRa Alliance has recently dedicated the specification for FUOTA, but the existing solution has several drawbacks, such as low energy efficiency, poor transmission reliability, and biased multicast grouping. In this paper, we propose a novel energy-efficient, reliable, and beamforming-assisted FUOTA system for LoRa networks named FLoRa, which is featured with several techniques, including delta scripting, channel coding, and beamforming. In particular, we first propose a novel joint differencing and compression algorithm to generate the delta script for processing gain, which unlocks the potential of incremental FUOTA in LoRa networks. Afterward, we design a concatenated channel coding scheme to enable reliable transmission against dynamic link quality. The proposed scheme uses a rateless code as outer code and an error detection code as inner code to achieve coding gain. Finally, we design a beamforming strategy to avoid biased multicast and compromised throughput for power gain. Experimental results on a 20-node testbed demonstrate that FLoRa improves network transmission reliability by up to 1.51 × and energy efficiency by up to 2.65 × compared with the existing solution in LoRaWAN.

Big data to use JAVA, group software engineering, networking, cloud computing knowledge and technology. The purpose of this paper is Research on Wireless sensor network of the Internet of things. The Internet of things, mainly includes multicast network, ZIGBEE network, WSN network, Bluetooth network, infrared network and so on. Swarm software engineering is a way to implement cloud computing, Internet of things and big data. Cloud computing comes from big data, the Internet of things can be achieved through cloud computing. This paper mainly studies, computers, software, networks, smart cities, and the use of Excel and Matlab and Microsoft Office Visio 2003 mapping and so forth. And through the practice of research methods, including automotive networking and smart city. What is the Internet of things, objects connected to the Internet is the Internet of things, cup networking, car networking. Things better than other networks, is composed of what objects, what composition, what nature, what innovation and superiority. The four key technologies of the Internet are widely used, and these four technologies are mainly RFID, WSN, M2M, two kinds of integration. RFID can be implemented using MATLAB, NS2, and JAVA, and WSN can be implemented using NS2, and M2M can be developed using JAVA. The research results are that the Internet of things originated and developed in the Internet; on the contrary, the development of the Internet of things further promoted the Internet to a more widespread “Internet” evolution. The Internet of things and the Internet are the relationships between the parent and the child. Wireless networks are just like wireless WSN networks, but wireless nodes are fixed and moved into sensors. The Internet of things includes Internet technology, including wired and wireless networks. The research conclusion is the wireless internet of things are just like the wired internet of things, wired provides the basis for Wireless Research. Baidu Tiangong Internet of things platform, Amazon AWS platform, ERP and so on are also important applications of the Internet of things. The use of mirroring and replication software also requires Internet of things. Video is composed of multi frame images. H.264 and JM encoder are also the future directions. Where to go network Ctrip network is the application of the Internet of things. Recalling what we do today, planning tomorrow, how to spend the university stage and predicting the future of university development can be the application of the Internet of things. I visited the Tangshan Rd. Mart store in Qian’an from January 2017 to March. The feeling is that Beijing is still Carrefour and Jing Kelong and WAL-MART and Hualian. The electricity supplier which Ma Yun’s Alibaba still feels more powerful. Now Hebei province and all parts of the country have venture capital and subsidy, which will undoubtedly promote the Internet of things.

The large deployment of Internet of Things (IoT) is actually enabling Smart City projects and initiatives all over the world. Objects used in daily life are being equipped with electronic devices and protocol suites in order to make them interconnected and connected to the Internet. According to a recent Gartner study, 50 billion connected objects have been deployed in smart cities by 2020. These connected objects will make our cities smart. However, they will also open up risks and privacy issues. As various smart city initiatives and projects have been launched in recent years, we have witnessed not only the expected benefits but the risks introduced. The current and future trends of smart city with respect to IoT have been described. It also discussed the interaction between smart cities and IoT. The drivers behind the evolution & development of IoT and smart cities have been explained. Finally, the IoT weaknesses and how they can be addressed when used for smart cities has been discussed

In the smart cities, objects can smartly communicate with the people through Internet of Things (IoT). It will make smart cities a greener place by detecting pollution through IoT and environmental sensors. In order to maintain the sustainability of green place in smart cities, the emerging technology, i.e. Green IoT automatically and intelligently makes smart cities sustainable in a collaborative manner. Governments and a lot of organizations around the world are doing a lot of efforts to campaign the importance of the reduction of energy consumption and carbon production as well as emphasize on the Green IoT for smart cities. Various IoT related smart cities architectures are already presented in literature. But this work presents the concept of the “Green IoT” to create a green environment which will apprehend the idea of energy saving in smart cities. In this chapter, design of Green IoT architecture is proposed for smart cites with the focus to reduce energy consumption at each stage and ensure realization of IoT toward green. This proposed Green IoT architecture is based on the cloud based system which reduces the hardware consumption.

The Internet of Things (IoT) is driving the technology and advances of the Internet and every day it is becoming more popular to talk about IoT systems in multiple domains: Smart Cities, Agriculture, and Industrial Internet, etc. Increasingly, IoT systems will need to interact and be interconnected for offering the always-promoted everything-connected paradigm. Current IoT systems rely on semantic web technologies for integrating data and ensure web services interoperability. However there are yet a gap to ensure semantic interoperability among IoT systems. Most of the existing proposed (open) approaches and solutions lack on formal methodologies for interoperability in technology and standard format of the data. We studied and analyzed most available semantic-based IoT approaches to identify the main requirements hindering IoT semantic interoperability. In this paper, we present SEG 3.0 a methodology to federate, unify and provide semantic interoperability. SEG 3.0 emerges from methodologies for ontology engineering and the idea of unification and federated systems. We propose SEG 3.0 and apply it to Internet of Things (IoT) and particularly on use cases for smart cities as proof of concept. Firstly, we define characteristics required for the methodology. Secondly, we describe the processes and the different formal steps. Thirdly, we provide a proof of concept framework and architecture applying this methodology, thus the benefits of using SEG 3.0 methodology in IoT domains are described. Finally, we demonstrate that the SEG 3.0 methodology is applied to three use cases: (1) the M3 framework to assist developers in designing semantic-based IoT applications, (2) the VITAL EU project for smart cities, and (3) the FIESTA-IoT EU project for IoT semantic interoperability. SEG 3.0 is a formal methodology generic enough to be applied to other domains than IoT and smart cities, since the main benefit of the SEG 3.0 is integrating heterogeneous data and adding value to it to build innovative applications.

The Internet of Things (IoT) has become one of the most transformative technologies in building the smart city concept. With the potential to connect diverse devices through internet networks, IoT enables increased efficiency in sectors such as transportation, energy and health. This research aims to explore the role of IoT in smart city implementation, highlighting its challenges and opportunities. Based on a literature review and empirical analysis, this research finds that although IoT can improve the quality of life in smart cities, there are several major challenges that must be overcome, such as security, scalability and interoperability issues. This article provides deeper insight into how to optimize IoT deployment to achieve urban sustainability. The novelty in this research lies in the integrative approach that combines the analysis of technical and non-technical challenges in IoT implementation in smart cities. This research also proposes practical solutions to overcome these challenges, such as the development of public policies that encourage IoT interoperability and security.

Smart cities, enabled by the Internet of Things (IoT), leverage technology to optimize urban living and enhance infrastructure. As urban environments become interconnected hubs of digital innovation, securing critical components like public transportation infrastructure becomes increasingly important. This research addresses the need for robust intrusion detection systems (IDS) tailored to the unique challenges of securing public transportation within smart cities. Focused on the Tabuk region in Saudi Arabia, the study introduces an IDS model integrating the deep maxout network with walrus optimization (DMN-WO). The DMN is configured with an architecture that includes multiple layers with maxout activation functions. These layers are capable of capturing complex patterns in the data, making the DMN particularly effective for identifying anomalies in IoT network traffic. The DMN-WO model is ensured to be resource-efficient and suitable for real-time deployment on constrained devices like Raspberry Pi, typical in IoT systems. Training and validation are conducted using the CIC-IDS-2018 dataset, CIC-IDS -2029 dataset and real-time data from Raspberry Pi devices deployed in the smart city's public transportation network. Real-time data application maintains robust performance, with 98.06% accuracy, 98.50% detection rate, 98.81% precision, 98.24% specificity, and a 98.57% F1-score. This research advances cybersecurity measures in smart city applications by providing a resilient solution for detecting and mitigating security threats in public transportation infrastructure. It lays the groundwork for further refinements and real-world deployments in the dynamic landscape of smart cities.