The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial Intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compares their corresponding results. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.
Shanghai Jiao Tong University（上海交通大学）；Macquarie University（麦考瑞大学）；University of Technology Sydney（悉尼科技大学）；Fuzhou University（福州大学）；Lulea University of Technology（吕勒奥理工大学）
The ever-increasing data traffic, various delay-sensitive services, and the massive deployment of energy-limited Internet of Things (IoT) devices have brought huge challenges to the current communication networks, motivating academia and industry to move to the sixth-generation (6G) network. With the powerful capability of data transmission and processing, 6G is considered as an enabler for IoT communication with low latency and energy cost. In this paper, we propose an artificial intelligence (AI) and intelligent reflecting surface (IRS) empowered energy-efficiency communication system for 6G…
Aalborg University（奥尔堡大学）；Siemens AG（西门子股份公司）；University of Oulu（奥卢大学）
An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting harvesting machines. Energy efficiency is key in such edge environments, since they are often based on an infrastructure that consists of wireless and battery-run devices, e.g., e-tractors, drones, Automated Guided Vehicle (AGV)s and robots. The total energy consumption draws contributions from multipleiIoTe technologies that enable edge computing and communicati…
Intelligent Duty Cycling Management and Wake-up for Energy Harvesting IoT Networks with Correlated Activity
Centre for Wireless Communications（无线通信中心）；University of Oulu（奥卢大学）；Instituto Universitario de Investigación y Desarrollo Tecnológico（大学技术研究与发展研究所）；Universidad Tecnológica Metropolitana（都市科技大学）；Aalborg University（奥尔堡大学）；University of Houston（休斯顿大学）
Key Lab of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications（北京邮电大学教育部泛在无线通信重点实验室）；Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong（香港中文大学系统工程与工程管理系）；Department of Operations Research and Financial Engineering, Princeton University（普林斯顿大学运筹学与金融工程系）；Shenzhen Research Institute of Big Data and The Chinese University of Hong Kong, Shenzhen（深圳市大数据研究院与香港中文大学（深圳））
The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more challenging but more useful in large-scale IoT. In this paper, we consider a voting-based MARL problem, in which the agents vote to make group decisions and the goal is to maximize the globally averaged returns. To this end, we formulate the MARL problem based on the linear programming form of the policy optimization problem and propose a distributed primal-dual algorithm to obtain the optimal solution. We also propos…
China University of Petroleum（中国石油大学）；Shandong University（山东大学）；Northeastern State University（东北州立大学）；Tongji University（同济大学）
At present, SOILD-STATE Fermentation (SSF) is mainly controlled by artificial experience, and the product quality and yield are not stable. Accurately predicting the quality and yield of SSF is of great significance for improving human food security and supply. In this paper, we propose an Intelligent Utility Prediction (IUP) scheme for SSF in 5G Industrial Internet of Things (IoT), including parameter collection and utility prediction of SSF process. This IUP scheme is based on the environmental perception and intelligent learning algorithms of the 5G Industrial IoT. We build a workflow model…
Chongqing University of Posts and Telecommunications（重庆邮电大学）；Carleton University（卡尔顿大学）
Vertical heterogenous networks (VHetNets) and artificial intelligence (AI) play critical roles in 6G and beyond networks. This article presents an AI-native VHetNets architecture to enable the synergy of VHetNets and AI, thereby supporting varieties of AI services while facilitating automatic and intelligent network management. Anomaly detection in Internet of Things (IoT) is a major AI service required by many fields, including intrusion detection, state monitoring, device-activity analysis, security supervision and so on. Conventional anomaly detection technologies mainly consider the anomal…
Indian Institute of Information Technology, Nagpur（那格浦尔印度信息技术学院）；Visvesvaraya National Institute of Technology, Nagpur（维斯瓦拉亚国家理工学院那格浦尔分校）
Intelligent resident surveillance is one of the most essential smart community services. The increasing demand for security needs surveillance systems to be able to detect anomalies in surveillance scenes. Employing high-capacity computational devices for intelligent surveillance in residential societies is costly and not feasible. Therefore, we propose anomaly detection for intelligent surveillance using CPU-only edge devices. A modular framework to capture object-level inferences and tracking is developed. To cope with partial occlusions, posture deformations, and complex scenes, we employed…
The expansion of the Internet of Things(IoT) services and a huge amount of data generated by different sensors, signify the importance of cloud computing services like Storage as a Service more than ever. IoT traffic imposes such extra constraints on the cloud storage service as sensor data preprocessing capability and load-balancing between data centers and servers in each data center. Also, it should be allegiant to the Quality of Service (QoS). The hybrid MWG algorithm has been proposed in this work, which considers different objectives such as energy, processing time, transmission time, an…
California State University Los Angeles（加州州立大学洛杉矶分校）
The Internet of Things (IoT) is continuously growing to connect billions of smart devices anywhere and anytime in an Internet-like structure, which enables a variety of applications, services and interactions between human and objects. In the future, the smart devices are supposed to be able to autonomously discover a target device with desired features and generate a set of entirely new services and applications that are not supervised or even imagined by human beings. The pervasiveness of smart devices, as well as the heterogeneity of their design and functionalities, raise a major concern: …
United International University（联合国际大学）；King Saud University（沙特国王大学）
Accidents in inland waterways in developing countries are a regular phenomenon throughout the year causing deaths, injuries, monetary loss, and a significant amount of missing people. In consequence, a lot of families are losing their dear ones leading to much misery. The above context demands an intelligent, safe, and reliable water transport system for the developing countries. The concept of Intelligent Transport System (ITS) can be applied to develop such system; however, there are issues with ITS and Internet of Things (IoT) unlocks a new way of developing it. This paper proposes a model …
Internet of Things (IoT) is emerging as a significant technology in shaping the future by connecting physical devices or things with internet. It also presents various opportunities for intersection of other technological trends which can allow it to become even more intelligent and efficient. In this paper we focus our attention on the integration of Intelligent Conversational Software Agents or Chatbots with IoT. Literature surveys have looked into various applications, features, underlying technologies and known challenges of IoT. On the other hand, Chatbots are being adopted in greater num…
Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology
Aqaba University of Technology（阿卡巴理工大学）；Concordia University（康考迪亚大学）；Khalifa University（哈利法大学）；The University of Jordan（约旦大学）；Applied Science Private University（应用科学私立大学）；King Fahd University of Petroleum & Minerals（法赫德国王石油与矿业大学）
The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing obstacles in this area. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart heal…
A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions
University of Luxembourg（卢森堡大学）；Nantes University（南特大学）；École Centrale Nantes（南特中央理工学院）；Politecnico di Torino（都灵理工大学）；University of Ulsan（蔚山大学）；University of Alabama in Huntsville（阿拉巴马大学亨茨维尔分校）；Trinity College Dublin, The University of Dublin（都柏林大学圣三一学院）
University of South Florida（南佛罗里达大学）；Electrical Engineering Department, University of South Florida（南佛罗里达大学电气工程系）；University of South Florida, Tampa, FL 33620, USA（南佛罗里达大学，美国佛罗里达州坦帕市，邮编33620）
Intelligent vehicular systems and smart city applications are the fastest growing Internet of things (IoT) implementations at a compound annual growth rate of 30%. In view of the recent advances in IoT devices and the emerging new breed of IoT applications driven by artificial intelligence (AI), fog radio access network (F-RAN) has been recently introduced for the fifth generation (5G) wireless communications to overcome the latency limitations of cloud-RAN (C-RAN). We consider the network slicing problem of allocating the limited resources at the network edge (fog nodes) to vehicular and smar…
