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Author

Mohd Abdul Ahad

Other affiliations: Hamdard University
Bio: Mohd Abdul Ahad is an academic researcher from Jamia Hamdard. The author has contributed to research in topics: Big data & Smart city. The author has an hindex of 10, co-authored 33 publications receiving 358 citations. Previous affiliations of Mohd Abdul Ahad include Hamdard University.

Papers
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Journal ArticleDOI
TL;DR: The role of enabling technologies in smart cities is reviewed and three categories of challenges are identified namely technical, socio-economic and environmental giving specifics of each category.

231 citations

Journal ArticleDOI
TL;DR: This paper presents the state-of-the-art blockchain technology to solve the security issues of smart cities and surveys the utility of blockchain in various smart communities such as healthcare, transportation, smart grid, supply chain management, financial systems and data center networks.

187 citations

Journal ArticleDOI
TL;DR: A comprehensive survey on security improvements achieved in IoT systems using blockchain and the challenges that originate during this integration and the most relevant blockchain based IoT applications are presented.

106 citations

Journal ArticleDOI
TL;DR: This paper explores the technological and social barriers in adoption of SHS by analyzing state-of-the-art expert views and user's perception and proposes a blockchain based SHS framework to provide intrinsic security and integrity of the system.

94 citations

Journal ArticleDOI
18 Mar 2021-Sensors
TL;DR: In this article, the authors provide an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it, including mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles.
Abstract: The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

67 citations


Cited by
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Journal ArticleDOI
14 Feb 2020-Sensors
TL;DR: A survey aimed at summarizing the current state of the art regarding smart irrigation systems, which determines the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions.
Abstract: Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.

264 citations

01 Jan 2007
TL;DR: In this paper, the relationship between following distance and velocity mapped into a two-dimensional space is modeled for each driver with an optimal velocity model approximated by a nonlinear function or with a statistical method of a Gaussian mixture model (GMM).
Abstract: | All drivers have habits behind the wheel. Different drivers vary in how they hit the gas and brake pedals, how they turn the steering wheel, and how much following distance they keep to follow a vehicle safely and comfortably. In this paper, we model such driving behaviors as car-following and pedal operation patterns. The relationship between following distance and velocity mapped into a two-dimensional space is modeled for each driver with an optimal velocity model approximated by a nonlinear function or with a statistical method of a Gaussian mixture model (GMM). Pedal operation patterns are also modeled with GMMs that represent the distributions of raw pedal operation signals or spectral features extracted through spectral analysis of the raw pedal operation signals. The driver models are evaluated in driver identification experiments using driving signals collected in a driving simulator and in a real vehicle. Experimental results show that the driver model based on the spectral features of pedal operation signals efficiently models driver individual differences and achieves an identification rate of 76.8% for a field test with 276 drivers, resulting in a relative error reduction of 55% over driver models that use raw pedal operation signals without spectral analysis.

236 citations

Journal ArticleDOI
TL;DR: The role of enabling technologies in smart cities is reviewed and three categories of challenges are identified namely technical, socio-economic and environmental giving specifics of each category.

231 citations

Journal ArticleDOI
TL;DR: A contemporary survey on the latest advancement in blockchain for IoV is presented, highlighting the different application scenarios of IoV after carefully reviewing the recent literature and investigating several key challenges.
Abstract: Internet of Vehicles (IoV) is an emerging concept that is believed to help realize the vision of intelligent transportation systems (ITSs). IoV has become an important research area of impactful applications in recent years due to the rapid advancements in vehicular technologies, high throughput satellite communication, the Internet of Things, and cyber–physical systems. IoV enables the integration of smart vehicles with the Internet and system components attributing to their environments, such as public infrastructures, sensors, computing nodes, pedestrians, and other vehicles. By allowing the development of a common information exchange platform between vehicles and heterogeneous vehicular networks, this integration aims to create a better environment and public space for the people as well as to enhance safety for all road users. Being a participatory data exchange and storage, the underlying information exchange platform of IoV needs to be secure, transparent, and immutable in order to achieve the intended objectives of ITS. In this connection, the adoption of blockchain as a system platform for supporting the information exchange needs of IoV has been explored. Due to their decentralized and immutable nature, IoV applications enabled by blockchain are believed to have a number of desirable properties, such as decentralization, security, transparency, immutability, and automation. In this article, we present a contemporary survey on the latest advancement in blockchain for IoV. Particularly, we highlight the different application scenarios of IoV after carefully reviewing the recent literature. We also investigate several key challenges where blockchain is applied in IoV. Furthermore, we present the future opportunities and explore further research directions of IoV as a key enabler of ITS.

192 citations

Journal ArticleDOI
TL;DR: Experimental results demonstrate the superiority of the PPSF framework over some recent approaches in blockchain and non-blockchain systems.
Abstract: With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of urbanization. IoT networks allow distributed smart devices to collect and process data within smart city infrastructure using an open channel, the Internet. Thus, challenges such as centralization, security, privacy (e.g., performing data poisoning and inference attacks), transparency, scalability, and verifiability limits faster adaptations of smart cities. Motivated by the aforementioned discussions, we present a Privacy-Preserving and Secure Framework (PPSF) for IoT-driven smart cities. The proposed PPSF is based on two key mechanisms: a two-level privacy scheme and an intrusion detection scheme. First, in a two-level privacy scheme, a blockchain module is designed to securely transmit the IoT data and Principal Component Analysis (PCA) technique is applied to transform raw IoT information into a new shape. In the intrusion detection scheme, a Gradient Boosting Anomaly Detector (GBAD) is applied for training and evaluating the proposed two-level privacy scheme based on two IoT network datasets, namely ToN-IoT and BoT-IoT. We also suggest a blockchain-InterPlanetary File System (IPFS) integrated Fog-Cloud architecture to deploy the proposed PPSF framework. Experimental results demonstrate the superiority of the PPSF framework over some recent approaches in blockchain and non-blockchain systems.

150 citations