1,720,990 research outputs found
AI-Powered Drone to Address Smart City Security Issues
No full textThe idea of a dazzling metropolis has drawn interest from all across the world. New innovations like blockchain, IoT, artificial intelligence, robots, and many other things were added to it. Security is one of the top issues for people living in big cities, and everyone wants to feel completely secure when traveling around every single day. In this research, we will look into how CEOs in affluent cities use and value robots, especially in terms of security. To understand the robot security the board stream, some approaches and intricacies are used. Following that is a discussion of issues with urban security and the application of artificial intelligence to drones as a management tool. The use of cutting-edge technology, such as blockchain, to support smart urban community management is covered in the last part. The smart city idea and all of its benefits for local inspection are supported by robotic use. The idea of thriving urban areas is spreading around the world and is crucial in the context of developing economies. We examined how to leverage cutting-edge technologies in this project to make it feasible. Artificial intelligence, robotics breakthroughs, and blockchain technologies all have significant effects. This research highlights their significance to analysts and how they consider them when assessing prospects. This project will be very beneficial for analysts and experts in a relevant subject
Applications of Artificial Intelligence and Machine learning in smart cities
No full textSmart cities are aimed to efficiently manage growing urbanization, energy consumption, maintain a green environment, improve the economic and living standards of their citizens, and raise the people's capabilities to efficiently use and adopt the modern information and communication technology (ICT). In the smart cities concept, ICT is playing a vital role in policy design, decision, implementation, and ultimate productive services. The primary objective of this review is to explore the role of artificial intelligence (AI), machine learning (ML), and deep reinforcement learning (DRL) in the evolution of smart cities. The preceding techniques are efficiently used to design optimal policy regarding various smart city-oriented complex problems. In this survey, we present in-depth details of the applications of the prior techniques in intelligent transportation systems (ITSs), cyber-security, energy-efficient utilization of smart grids (SGs), effective use of unmanned aerial vehicles (UAVs) to assure the best services of 5G and beyond 5G (B5G) communications, and smart health care system in a smart city. Finally, we present various research challenges and future research directions where the aforementioned techniques can play an outstanding role to realize the concept of a smart city
Quantifying uncertainty in internet of medical things and big-data services using intelligence and deep learning
Full text linkIn the cloud-based Internet of Things (IoT) environments, quantifying uncertainty is an important element input to keep the acceptable level of reliability in various configurations. In this paper, we aim to address the pricing model of delivering data over the cloud while taking into consideration the dynamic uncertainty factors such as network topology, transmission/reception energy, nodal charge and power, and computation capacity. These uncertainty factors are mapped to different nodes with varying capabilities to be processed using Artificial Intelligence (AI)-based algorithms. Accordingly, we aim to find a way to calculate and predict the price per big data service over the cloud using AI and deep learning. Therefore, in this paper, we propose a framework to address big data delivery issues in cloud-based IoT environments by considering uncertainty factors. We compare the performance of the framework using two AI-based techniques called Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA) in both centralized and distributed versions. The use of AI techniques can be applied in multilevel to provide a kind of deep learning to further improve the performance of the system under study. The results reveal that the distributed algorithm outperforms the centralized one. In addition, the results show that the GA has lower running time compared to the SAA in all the test cases such as 68% of improvement in the centralized version, and 66% of improvement in the distributed version in case when the size of uncertainty array is 256. Moreover, when the size of uncertainty array increases, the results show 60% speed up in the distributed GA compared to its centralized version. The improvements achieved would help the service providers to actually improve their profit using the proposed framework
Share: A Design Pattern for Dynamic Composition of IoT Services
No full textThe Internet-of-Things (IoT) is one of the modern technological revolutions that enables communication amongst a plethora of different devices. To date 30 billion devices are connected to the internet more than 75 billion devices are foreseen to be connected worldwide by 2025, a five fold increase in ten years. Devices can have different brands and developers and can be designed to function on a proprietary ecosystem, with separate applications, gateways and tools to support them. This fragmentation can be disastrous in certain industries, such as the medical ones, and limit integration between different systems. In this paper, we envision a solution to overcome this interaction problems. We propose Share a novel programming standard through a design pattern. This allows on the fly service composition of resource constrained IoT devices. To this ending, IoT devices exchange integration codes which specify the data format and the interaction protocol. The design by contract scheme (DCS) is used to make sure that the matching services verify the constraints dictated by the composition. Unlike other on the fly approaches, Share can run on very small and resource constrained devices. Share has been implemented by using LUA programming language and has been validated on the ESP30 embedded device
Seamless secure anonymous authentication for cloud-based mobile edge computing
No full textDue to technological advancement and deployment of handheld devices, mobile computing devices have gained the user attention to save resource usage, service access, and application use. In practice, it can be deployed widely to experience massive data storage and less computation cost. However, wireless channel access is vulnerable and insecure to prevent various potential attacks such as replay, redirection, etc. As a consequence, a seamless secure anonymous authentication scheme (S-SAAS) is proposed to create a secure session in cloud-based mobile edge computing. Since IoT, cloud computing, big-data and mobile technologies are converged to permit the group-based communication systems, it is highly demanded to strengthen the authentication process in order to reduce the security risk and vulnerabilities. Moreover, the experimental analysis proves that the proposed S-SAAS scheme consumes less signaling congestion and routing control overhead to achieve better service connection rate
A Hash-Based RFID Authentication Mechanism for Context-Aware Management in IoT-Based Multimedia Systems
Full text linkWith the technological advances in the areas of Machine-To-Machine (M2M) and Device-To-Device (D2D) communication, various smart computing devices now integrate a set of multimedia sensors such as accelerometers, barometers, cameras, fingerprint sensors, gestures, iris scanners, etc., to infer the environmental status. These devices are generally identified using radio-frequency identification (RFID) to transfer the collected data to other local or remote objects over a geographical location. To enable automatic data collection and transition, a valid RFID embedded object is highly recommended. It is used to authorize the devices at various communication phases. In smart application devices, RFID-based authentication is enabled to provide short-range operation. On the other hand, it does not require the communication device to be in line-of-sight to gain server access like bar-code systems. However, in existing authentication schemes, an adversary may capture private user data to create a forgery problem. Also, another issue is the high computation cost. Thus, several studies have addressed the usage of context-aware authentication schemes for multimedia device management systems. The security objective is to determine the user authenticity in order to withhold the eavesdropping and tracing. Lately, RFID has played a significant for the context-aware sensor management systems (CASMS) as it can reduce the complexity of the sensor systems, it can be available in access control, sensor monitoring, real time inventory and security-aware management systems. Lately, this technology has opened up its wings for CASMS, where the challenging issues are tag-anonymity, mutual authentication and untraceability. Thus, this paper proposes a secure hash-based RFID mechanism for CASMS. This proposed protocol is based on the hash operation with the synchronized secret session-key to withstand any attacks, such as desynchronization, replay and man-in-the-middle. Importantly, the security and performance analysis proves that the proposed hash-based protocol achieves better security and performance efficiencies than other related schemes. From the simulation results, it is observed that the proposed scheme is secure, robust and less expensive while achieving better communication metrics such as packet delivery ratio, end-to-end delay and throughput rate
Intelligent data delivery approach for smart cities using road side units
Full text linkSmart city progress from classical homogenous technologies with limited facility to heterogeneous interconnected network with immense capabilities. Furthermore, there is a good concern in expanding the scope of application in the smart city. The primary objective of the smart city is to achieve optimization and reinforce the Quality of Service (QoS) of applications by cleverer usage of urban resources. The QoS in the network is measured using several factors like end-end delay, energy consumption, packet loss and throughput. Several pitfalls are experienced in the existing routing innovation. In this proposal, a new technology-based routing structure is proposed. Road Side Units (RSU) will allow the planners to deploy the application without unfamiliar tools for data process and gathering. Data forwarding, acquisition and diffusion are simplified by RSU. K-Nearest Neighbor is used for finding the nearest neighbor nodes and it is optimized using Whale optimization Algorithm (WOA). The evaluation outcomes prove that the intended routing plot provides much spectacle than existing protocols for real time applications
Classification of IoT Device Communication Through Machine Learning Techniques
No full textThe Internet of Things (IoT) also called the Internet of Everything is a system of smart interconnected devices. The smart devices are uniquely identifiable over the network and perform autonomous data communication over the network with or without human-to-computer interaction. These devices have a high level of diversity, heterogeneity, and operates with various computational capabilities. It is highly necessary to develop a framework that allows to classify the devices into different categories from effective management, security, and privacy perspectives. Various solutions such as network traffic analysis, network protocols analysis, etc. have been developed to solve the problem of device classification. The signal of a device is an important feature that could be utilized to classify various network devices. We propose a framework to identify network devices based on their signal analysis. We have developed a training data set, by collecting signals from various Wi-Fi and Bluetooth devices in a specific geographic area. A machine learning-based model is proposed for the prediction of network device classification (e.g., a Wi-Fi or Bluetooth device) with 100% accuracy. Furthermore, clustering techniques are applied to the acquired signals to predict the total number of active Wi-Fi devices in a given region
BAIV: An Efficient Blockchain-Based Anonymous Authentication and Integrity Preservation Scheme for Secure Communication in VANETs
No full textRecent development in intelligent transport systems (ITS) has led to the improvement of driving experience in vehicular ad-hoc network (VANET) systems. Providing a low computational cost with high serving capability, however, is a critical phenomenon in the current VANET system. In the existing scenario, when the authenticated vehicle user moves from one roadside unit (RSU) to another RSU region, re-authentication of the vehicle user is required by the current RSU, which increases the computational complexity. To overcome the above-mentioned challenge, a blockchain-based authentication protocol is developed in this work. In this suggested process, blockchain is integrated with VANET, which enables the authentication of the vehicle user without the involvement of a trusted authority. Moreover, the integrity of the message and privacy of vehicle users are preserved in the blockchain network. Even though many blockchain-based schemes have been proposed recently, the existing schemes were not focused on conditional anonymity. However, in our proposed scheme, conditional privacy is introduced to revoke the malicious vehicles in the case of disputes and to avoid further damage to the VANET system. As a result, the proposed scheme provides an efficient mechanism for anonymous authentication, privacy, and integrity preservation with conditional tracking. Finally, the defense against different security threats is explained in the security analysis section, and the performance investigation section shows the competence and efficacy of our method with similar related methods
Light Communication for Controlling Industrial Robots
Full text linkOptical Wireless Communication (OWC) is regarded as an auspicious communication approach that can outperform the existing wireless technology. It utilizes LED lights, whose subtle variation in radiant intensity generate a binary data stream. This is perceived by a photodiode, that converts it to electric signals for further interpretation. This article aims at exploring the use of this emerging technology in order to control wirelessly industrial robots, overcoming the need for wires, especially in environments where radio waves are not working due to environmental factors or not allowed for safety reasons. We performed experiments to ensure the suitability and efficiency of OWC based technology for the aforementioned scope and “in vitro" tests in various Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) configurations to observe the system throughput and reliability. The technology performance in the “clear LoS" and in the presence of a transparent barrier, were also analyzed
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