Internet Of Things Based Smart City Research Articles

LSM: A Lightweight Security Mechanism for IoT Based Smart City Management Systems using Blockchain

Smart cities utilize digital technologies for the improvement of its services’ quality and performance by reducing resources’ cost and consumption, with a commitment of action and efficiency to its citizens. The increased urban migration has led to many problems in cities, such as traffic congestion, waste management, noise pollution, energy consumption, air pollution, etc., as nowadays COVID-19 pandemic has seized the whole world. So, it is necessary to carry out its standard operating procedures (SOPs), including less human interaction. Thus, technology plays a vital role via Internet-of-Things (IoT) based systems. In this paper, a lightweight security mechanism (LSM) is proposed to enrich the IoT based systems. Blockchain technology is integrated, and its completely decentralized peer-to-peer (P2P) technology enables the users’ authentication and authorizes legitimate procedures. The IoT based management system is developed to monitor some of the aforementioned problems and solve solid waste, air, and noise monitoring systems. The Ethereum blockchain is used to implement a smart contract based framework for the system’s security and access control. The evaluation of performance of the LSM demonstrates that it is an efficient and lightweight tool in terms of cost, resources, and computation and superior over related security studies.

Blockchain based secure smart city architecture using low resource IoTs

Internet of Things (IoT) is growing exponentially in research and industry. Although, many standard and conventional security solutions have been provided for IoT, it suffers from many privacy and security concerns. Standard security protocols are not suitable for majority of IoT devices because of its decentralized topology and resource-constraints. Blockchain (BC) finds its efficient application in IoT to preserve the five basic cryptographic primitives, such as confidentiality, authenticity, integrity, availability and non-repudiation. Adoption of conventional BC in IoT causes high energy consumption, delay and computational overheads which are not appropriate for various resource constrained IoT devices. To mitigate these problems, this work proposes a smart access control framework in a public and a private BC for a smart city application which makes it more efficient and secure as compared to the existing IoT applications. The proposed IoT based smart city architecture adopts BC technology for preserving all the cryptographic security and privacy issues. Moreover, proposed BC has minimal overhead as well. This work investigates the existing threat models and critical access control issues which handle multiple permissions of various processing nodes of IoT environment and detects relevant inconsistencies. Comparison in terms of all security issues with existing literature shows that the proposed architecture is competitively efficient in terms of security access control. The primary goal of this research article is to explore the possibility of BC as an alternative to standard security solutions for low resource IoT applications.

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

Internet of Things (IoT) is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The IoT for Smart Cities has many different domains and draws upon various underlying systems for its operation. In this paper, we provide a holistic coverage of the Internet of Things in Smart Cities. We start by discussing the fundamental components that make up the IoT based Smart City landscape followed by the technologies that enable these domains to exist in terms of architectures utilized, networking technologies used as well as the Artificial Algorithms deployed in IoT based Smart City systems. This is then followed up by a review of the most prevalent practices and applications in various Smart City domains. Lastly, the challenges that deployment of IoT systems for smart cities encounter along with mitigation measures.

An efficient framework using visual recognition for IoT based smart city surveillance.

Smart city surveillance systems are the battery operated light weight Internet of Things (IoT) devices. In such devices, automatic face recognition requires a low powered memory efficient visual computing system. For these real time applications in smart cities, efficient visual recognition systems are need of the hour. In this manuscript, efficient fast subspace decomposition over Chi Square transformation is proposed for IoT based on smart city surveillance systems. The proposed technique extracts the features for visual recognition using local binary pattern histogram. The redundant features are discarded by applying the fast subspace decomposition over the Gaussian distributed Local Binary Pattern (LBP) features. This redundancy is major contributor to memory and time consumption for battery based surveillance systems. The proposed technique is suitable for all visual recognition applications deployed in IoT based surveillance devices due to higher dimension reduction. The validation of proposed technique is proved on the basis of well-known databases. The technique shows significant results for all databases when implemented on Raspberry Pi. A comparison of the proposed technique with already existing/reported techniques for the similar applications has been provided. Least error rate is achieved by the proposed technique with maximum feature reduction in minimum time for all the standard databases. Therefore, the proposed algorithm is useful for real time visual recognition for smart city surveillance.

Improving communication precision of IoT through behavior-based learning in smart city environment

Internet of Things (IoT) is an emergent heterogeneous communication platform that provides ubiquitous access to resources and meets the user demands. Developing smart city paradigm employs this communication platform for providing services to the users and granting distributed resource sharing. Mitigating adversary device selection in this platform prevents irrelevant data exchange and eases information access and exchange. External and internal communication hindering factors needs to be addressed to sustain uninterrupted communication. To improve the precision in communication security, an observation-based security system is modeled in this manuscript. This security system observes the local and global behavioral change in IoT device communication. The local and global behavioral changes are defined using device attributes and behavior modeling. The device and service provider input observations are processed by a neural network-based learning scheme to identify errors in the resource access. The communicating users and IoT devices are secured by selecting reputed service providers and data sources to improve the distributed resource utilization in IoT based smart city. The performance of the proposed scheme balances between security and resource utilization requirements of the users by reducing response loss and non-reputed device selection.

Cross‐layer routing protocol for event‐driven M2M communication in IoT‐assisted Smart City Planning and Management: CWSN‐eSCPM

The robustness of wireless sensor networks (WSNs) has broadened the use of wireless communication systems for modern machine-to-machine (M2M) communication. Internet-of-Things (IoT) being one of the most explored technologies has gained wide attention due to low-cost WSN communication systems. IoT is one of the dominant technologies used in Smart City implementation demands better communication paradigm including mobility assisted transmission paradigms; however, native IEEE 802.15.4 standard does not have mobility provision that limits its use for real-time applications. On contrary, implementing mobility with classical WSN might impose significantly great topological changes and node or network condition variations which cannot be dealt with the traditional reactive routing approach. Incorporating node and/or network awareness with proactive network management can enable classical WSN to support mobility, which can be vital for IoT based Smart City Planning and Management (SCPM). With this motivation, in this study, a robust Cross-Layer Architecture based WSN Routing Protocol for Event-Driven M2M Communication in SCPM (CWSN-eSCPM) is developed. CWSN-eSCPM encompasses Proactive Node Management Strategy, Data-Centric Service Differentiation and Fair Resource Scheduling (DCSDFRS), Packet Velocity Estimation, Cumulative Congestion Estimation, Dynamic Link Assessment that enables optimal Best Forwarding Node selection for deadline sensitive and reliable data communication. CWSN-eSCPM applies dynamic link quality, cumulative congestion degree, and packet velocity of a node to enable optimal routing decision. DCSDFRS enables optimal resource provision to the real-time data while assuring maximum possible resource for non-real-time data that assures Quality of Service provision for event-driven critical communication in SCPM. Noticeably, CWSN-eSCPM protocol has been applied on top of IEEE 802.15.4 protocol standard, while preserving backward compatibility feature, it can be used for WSN assisted communication purposes. The authors' proposed protocol has performed better in terms of packet delivery ratio, packet loss ratio and deadline miss ratio for both real-time data as well as non-real-time data.

Co-simulation Based Finite State Machine for Telematic and Data Compression Microservices in IoT

Despite the wide adoption of Internet of things (IoT) with several webs standards and cloud technologies; building of city wide IoT based smart city platform for solving transportation problem remains a daunting task. Owing to the dynamic nature of IoT and components of transportation systems, smart city architecture would require development of a scalable, distributed and evolving architecture on the web. With the advancement in autonomous transportation system there is a need for in adaptive module in telematic system for compressing the huge volume of commands and co-simulation mechanism to communicate with other sensor nodes etc. As IoT based microservices have special requirements of which are related to the size and type of information to be exchanged between end to end devices and the control centre. By the time the data makes its way to the cloud for analysis, the opportunity to act on it might be gone. Thus handling such huge streams of data on the fly is a daunting task. In this study we present a method for simultaneous co-simulation and run length encoding based compression for a wide network of mobile IoT framework running multimedia microservices based telematic system.

IoT Based Smart City with Vehicular Safety Monitoring

A definition of a smart city can be defined as a city which works smartly, reduce human effort, and collects data from the various parameters that include students, devices, water supply network, classes, labs, transportation, information system, etc. and analysis the data for the future work. Our internet of things (IoT) based stimulated and conceptual model consists of various systems which collect data from the different parameters and send data to the central control room through the access point. Various sensors are used for different environment parameter which is controlled by the microcontroller unit (MCU). These systems are centrally controlled and managed. Each system has its limit or levels respectively. If data crosses the limit, then our model activates the alert system which is installed in different location of the city. The alert system also displays the precautions and safety tricks for public information. The collected data are stored in a central repository for the data analysis. The collected data are displayed for public information which is deployed in a different location. Our smart city model consists of web & speed monitoring system which includes a radar system to measure the vehicles speed. If the speed of a vehicle crosses the speed limit then web/CCTV camera gets activated and captures the video/imagery data of the responsible vehicle and collects the information like vehicle color, vehicle types, vehicle number, etc. and sent to the central control room. Central control room broadcast the information to the management so that the responsible vehicle can be caught.

Edge computing framework for enabling situation awareness in IoT based smart city

The Internet of Things (IoT) offers a lot of benefits for building smart cities. Such cities will be able to utilize a huge number of heterogeneous IoT devices that can generate a sheer volume of data. So, considering this heterogeneity, one of the major challenges in smart cities is how to process this data and identify different situations for decision-makers on the basis of this data. The traditional cloud computing approach can provide enormous computing and storage facilities to support data processing. However, it requires all the data to be moved to the cloud from the edge devices of the user endpoint, thus introducing a high latency. In this paper, we used the edge computing approach to minimize such latency. Besides, as major portion of data is generated from the user endpoint, processing this data in the edge can significantly improve the performance. Our experiment shows that processing raw IoT data at the edge devices is effective in terms of latency and provides situational awareness for the decision makers of smart city in a seamless fashion.

Provably secure pseudo-identity based device authentication for smart cities environment

IoT based smart city idea is evolving with an intention of improving the quality of citizens’ life by practicing information and communication technologies. Smart city concept is believed to be possible by integrating the evolving technologies such as internet of things (IoT), automation and machine learning in which IoT holds the key role. Authentication has already been identified as a foremost security concern around the IoT, as millions of small devices go online and begin to share their data. Authentication in IoT environment mainly considers the three types of communications: IoT device – IoT device, IoT device – IoT gateway, and IoT gateway – mobile client. In this paper, we design a protocol to address the authentication process between IoT gateway and mobile client. The proposed protocol's security is analyzed formally and informally to demonstrate robustness. Performance analysis of the proposed protocol has also paid adequate attention to show the probability of implementation in real time applications.