Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way to creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.

With the introduction of Cyber-Physical Systems (CPS) and Internet of Things (IoT) technologies, the automation industry is undergoing significant changes, particularly in improving production efficiency and reducing maintenance costs. Industrial automation applications often need to transmit time- and safety-critical data to closely monitor and control industrial processes. Several Ethernet-based fieldbus solutions, such as PROFINET IRT, EtherNet/IP, and EtherCAT, are widely used to ensure real-time communications in industrial automation systems. These solutions, however, commonly incorporate additional mechanisms to provide latency guarantees, making their interoperability a grand challenge. The IEEE 802.1 Time-Sensitive Networking (TSN) task group was formed to enhance and optimize IEEE 802.1 network standards, particularly for Ethernet-based networks. These solutions can be evolved and adapted for cross-industry scenarios, such as large-scale distributed industrial plants requiring multiple industrial entities to work collaboratively. This paper provides a comprehensive review of current advances in TSN standards for industrial automation. It presents the state-of-the-art IEEE TSN standards and discusses the opportunities and challenges of integrating TSN into the automation industry. Some promising research directions are also highlighted for applying TSN technologies to industrial automation applications.

The adoption of real-time wireless technologies within the ever-growing field of networked industrial control systems is continuously gaining popularity. Widespread sensing and actuation devices based on high-throughput wireless standards allow for an increased system mobility and lower configuration and maintenance costs. The IEEE 802.11 standard, especially in its most recent amendments, pushes performance to a very high level, theoretically approaching those of the most common real-time Ethernet networks. Its nondeterministic communication behavior, however, makes 802.11 unsuitable for mission- and safety-critical applications with high-reliability requirements, at least in its standard form. In this paper, we present several major solutions that tackled this issue to achieve real-time and reliability guarantees in wireless networked control systems, capitalizing on the strong efforts devoted to the adoption of IEEE 802.11 physical layer (PHY) technologies. We first provide a deep analysis of the 802.11 protocols in order to propose guidelines toward smart parameter selection at the data-link layer (DLL). In addition, the design of effective rate selection algorithms is considered as a way of increasing both the timeliness and reliability of data delivery. A further systematic solution is represented by real-time (RT)-WiFi, a new time-division multiple-access (TDMA)-based highly configurable DLL protocol that enables high-speed hard real-time data exchange over 802.11 networks. An important goal of this paper is also to provide a thorough comparison among different discussed solutions, in order to put in evidence their advantages and disadvantages, possibly in relation with systems based on different underlying PHYs. We will finally highlight the open challenges and future directions in this active research field.

The world is experiencing an unprecedented, enduring, and pervasive aging process. With more people who need walking assistance, the demand for lower-extremity gait rehabilitation has increased rapidly over the years. The current clinical gait rehabilitative training requires heavy involvement of both medical doctors and physical therapists and thus are labor-intensive, subjective and expensive. To address these problems, advanced automation techniques, especially along with the proliferation of smart sensing and actuation devices and big data analytics platforms, have been introduced into this field to make the gait rehabilitation convenient, efficient, and personalized. This survey paper provides a comprehensive review on recent technological advances in wearable sensors, biofeedback devices and assistive robots. Empowered by the emerging networking and computing technologies in the big data era, these devices are interconnected into smart and connected rehabilitation systems to provide non-intrusive and continuous monitoring of physical and neurological conditions of the patients, perform complex gait analysis and diagnosis, and allow real-time decision making, biofeedback, and control of assistive robots. For each technology category, a detailed comparison among the existing solutions is provided. A thorough discussion is presented on remaining open problems and future directions to further improve the safety, efficiency and usability of the technologies.

Real-time wireless networks (RTWNs) are fundamental to many Internet-of-Things (IoT) applications. RTWNs typically apply time-division multiple access (TDMA)-based media access control mechanisms and often demand deterministic end-to-end packet delivery to meet the given quality of service (QoS) requirements. Packet scheduling in an RTWN thus plays a critical role for achieving the desired performance but is a challenging problem especially when the RTWN is large and must deal with multiple unexpected disturbances occurring concurrently. This paper introduces a novel distributed dynamic packet scheduling framework, D2-PaS. D2-PaS is capable of processing disturbances and minimizes the number of dropped packets while ensuring that all critical events due to disturbances are handled by their deadlines. As a distributed approach, D2-PaS constructs schedules locally at individual nodes, which significantly reduces the amount of schedule-related information to be broadcast by the gateway. As a dynamic approach, D2-PaS applies a lightweight packet dropping algorithm to determine on-line at the gateway which packets can be dropped in response to disturbances and disseminate this information to the network. D2-PaS has been implemented on a multi-hop RTWN testbed to validate its applicability on hardware and a popular RTWN stack. Both testbed measurements and extensive simulation results demonstrate the effectiveness of D2-PaS.