Today, vehicles are increasingly being connected to the Internet of Things which enable them to provide ubiquitous access to information to drivers and passengers while on the move. However, as the number of connected vehicles keeps increasing, new requirements (such as seamless, secure, robust, scalable information exchange among vehicles, humans, and roadside infrastructures) of vehicular networks are emerging. In this context, the original concept of vehicular ad-hoc networks is being transformed into a new concept called the Internet of Vehicles (IoV). We discuss the benefits of IoV along with recent industry standards developed to promote its implementation. We further present recently proposed communication protocols to enable the seamless integration and operation of the IoV. Finally, we present future research directions of IoV that require further consideration from the vehicular research community.

Throughout the last century, the automobile industry achieved remarkable milestones in manufacturing reliable, safe, and affordable vehicles. Because of significant recent advances in computation and communication technologies, autonomous cars are becoming a reality. Already autonomous car prototype models have covered millions of miles in test driving. Leading technical companies and car manufacturers have invested a staggering amount of resources in autonomous car technology, as they prepare for autonomous cars’ full commercialization in the coming years. However, to achieve this goal, several technical and non-technical issues remain: software complexity, real-time data analytics, and testing and verification are among the greater technical challenges; and consumer stimulation, insurance management, and ethical/moral concerns rank high among the non-technical issues. Tackling these challenges requires thoughtful solutions that satisfy consumers, industry, and governmental requirements, regulations, and policies. Thus, here we present a comprehensive review of state-of-the-art results for autonomous car technology. We discuss current issues that hinder autonomous cars’ development and deployment on a large scale. We also highlight autonomous car applications that will benefit consumers and many other sectors. Finally, to enable cost-effective, safe, and efficient autonomous cars, we discuss several challenges that must be addressed (and provide helpful suggestions for adoption) by designers, implementers, policymakers, regulatory organizations, and car manufacturers.

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

Rapid technological advances have revolutionized the industrial sector. Internet of Things (IoT), which has emerged a few years ago, has been embraced by industry, resulting in what is known as the Industrial Internet of Things (IIoT). Restricting the definition of IIoT to manufacturing yields another subset of IoT, known as Industry 4.0. IIoT and Industry 4.0 will consist of sensor networks, actuators, robots, machines, appliances, business processes, and personnel. Hence, a lot of data of diverse nature would be generated. The industrial process requires most of the tasks to be performed locally because of delay and security requirements, and structured data to be communicated over the Internet to web services and the cloud. To achieve this task, middleware support is required between the industrial environment and the cloud/web-services. In this context, fog is a potential middleware that can be very useful for different industrial scenarios. Additionally, as industrial big data is often unstructured, it can be trimmed and refined by the fog locally, before sending it to the cloud. We present an architectural overview of IIoT and Industry 4.0. We discuss how fog can provide local computing support in the IIoT environment and the core elements and building blocks of IIoT. We also present a few interesting prospective use cases of IIoT. Finally, we discuss some emerging research challenges related to IIoT.

Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

The rapid growth of the Internet of Things (IoT) has accelerated strong interests in the development of low-power wireless sensors. Today, wireless sensors are integrated within IoT systems to gather information in a reliable and practical manner to monitor processes and control activities in areas such as transportation, energy, civil infrastructure, smart buildings, environment monitoring, healthcare, defense, manufacturing, and production. The long-term and self-sustainable operation of these IoT devices must be considered early on when they are designed and implemented. Traditionally, wireless sensors have often been powered by batteries, which, despite allowing low overall system costs, can negatively impact the lifespan and the performance of the entire network they are used in. Energy Harvesting (EH) technology is a promising environment-friendly solution that extends the lifetime of these sensors, and, in some cases completely replaces the use of battery power. In addition, energy harvesting offers economic and practical advantages through the optimal use of energy, and the provisioning of lower network maintenance costs. We review recent advances in energy harvesting techniques for IoT. We demonstrate two energy harvesting techniques using case studies. Finally, we discuss some future research challenges that must be addressed to enable the large-scale deployment of energy harvesting solutions for IoT environments.