Cyber-Physical Systems (CPS) drive Industry 4.0 by integrating physical processes with digital control and communication. While conventional deployments heavily rely on Internet of Things (IoT) sensors for monitoring and automation, these setups can incur excessive hardware overhead and fragmented data flows. In contrast, Integrated Sensing and Communication (ISAC) offers a promising alternative by reusing communication signals to perform sensing without dedicated sensor hardware. ISAC can be used in CPS to reduce overhead, improve real-time situational awareness, and enable advanced industrial applications. This paper explores how ISAC can be incorporated into a 6 G architecture for smart factories, highlighting new network functions to coordinate sensing activities and manage Sensing Data. Through a detailed use case and reference architecture, we identify key challenges, including resource allocation, data fusion, distributed computing, and coordination among 6 G entities. We then propose techniques for resource- and energy-efficient data collection and predictive sensing, demonstrating their viability via an example tracking scenario. This work provides insights into the design choices and opens research areas for future 6 G systems aiming to unify sensing and communication within CPS.

Measuring rotation speed is essential to many engineering applications; it elicits faults undetectable by vibration monitoring alone and enhances the vibration signal analysis of rotating machines. Optical, magnetic or mechanical Tachometers are currently state-of-art. Their limitations are they require line-of-sight, direct access to the rotating object. This paper proposes RFTacho, a rotation speed measurement system that leverages novel hardware and signal processing algorithms to produce highly accurate readings con-veniently. RFTacho uses RF Orbital Angular Momentum (OAM) waves to measure rotation speed of multiple machines simultane-ously with no requirements from the machine's properties. OAM antennas allow it to operate in high-scattering environments, com-monly found in industries, as they are resilient to de-polarization compared to linearly polarized antennas. RFTacho achieves this by using two novel signal processing algorithms to extract the rotation speed of several rotating objects simultaneously amidst noise arising from high-scattering environments, non-line-of-sight scenarios and dynamic environmental conditions with a resolution of 1rpm. We test RFTacho on several real-world machines like fans, motors, air conditioners. Results show that RFTacho has avg. error of < 0.5% compared to ground truth. We demonstrate RFTacho's simultaneous multiple-object measurement capability that other tachometers do not have. Initial experiments show that RFTacho can measure speeds as high as 7000 rpm (theoretically 60000 rpm) with high resiliency at different coverage distances and orientation angles, requiring only 150 mW transmit power while operating in the 5 GHz license-exempt band. RFTacho is the first RF-based sensing system that combines OAM waves and novel processing approaches to measure the rotation speed of multiple machines simultaneously in a non-intrusive way.

LoRaWAN deployments follow anad hocdeployment model that has organically led to overlapping communication networks, sharing the wireless spectrum, and completely unaware of each other. LoRaWAN uses ALOHA-style communication where it is almost impossible to schedule transmission between networks belonging to different owners properly. The inability to schedule overlapping networks will cause internetwork interference, which will increase node-to-gateway message losses and gateway-to-node acknowledgment failures. This problem is likely to get worse as the number of LoRaWAN networks increases. In response to this problem, we propose IRONWAN, a wireless overlay network that shares communication resources without modifications to underlying protocols. It utilizes the broadcast nature of radio communication and enables gateway-to-gateway communication to facilitate the search for failed messages and transmit failed acknowledgments already received and cached in overlapping network’s gateways. IRONWAN uses two novel algorithms: 1) a real-time message interarrival predictor, to highlight when a server has not received an expected uplink message and 2) the interference predictor, to ensure that extra gateway-to-gateway communication does not negatively impact the communication bandwidth. We evaluate IRONWAN on a 1000-node simulator with up to ten gateways and a 10-node testbed with 2-gateways. The results show that IRONWAN can achieve up to 12% higher packet delivery ratio (PDR) and total messages received per node while increasing the minimum PDR by up to 28%. These improvements save up to 50% node’s energy. Finally, we demonstrate that IRONWAN has comparable performance to an optimal solution (wired and centralized) but with 2–32 times lower communication costs. IRONWAN also has up to 14% better PDR when compared to FLIP, a wired-distributed gateway-to-gateway protocol in certain scenarios.

Several engineering applications require reliable rotation speed measurement for their correct functioning. The rotation speed measurements can be used to enhance the machines' vibration signal analysis and can also elicit faults undetectable by vibration monitoring alone. The current state of the art sensors for rotation speed measurement are optical, magnetic and mechanical tachometers. These sensors require line-of-sight and direct access to the machine which limits their use-cases. In this demo, we showcase Cognisense, an RF-based hardware-software sensing system that uses Orbital Angular Momentum (OAM) waves to accurately measure a machine's rotation speed. Cognisense uses a novel compact patch antenna in a monostatic radar configuration capable of transmitting and receiving OAM waves in the 5GHz license-exempt band. The demo will show Cognisense working on machines with varied numbers of blades, sizes and materials. We will also present how Cognisense operates reliably in non-line-of-sight scenarios where traditional tachometers fail. We demonstrate how Cognisense works well in high-scattering scenarios and is not impacted by the material of rotor blades. Unlike optical tachometers that require one to face the machine head-on, Our demo will also show Cognisense performing reliably in the presence of a tilt angle between the system and the machine which is not possible with optical tachometers.

Wide Area Cyber-Physical Systems (WA-CPSs) are a class of control systems that integrate low-powered sensors, heterogeneous actuators, and computer controllers into large infrastructure that span multi-kilometre distances. Current wireless communication technologies are incapable of meeting the communication requirements of range and bounded delays needed for the control of WA-CPSs. To solve this problem, we use a Control Communication Co-design approach for WA-CPSs, that we refer to as the C 3 approach, to design a novel Low-Power Wide Area (LPWA) MAC protocol called Ctrl-MAC and its associated event-triggered controller that can guarantee the closed-loop stability of a WA-CPS. This is the first article to show that LPWA wireless communication technologies can support the control of WA-CPSs. LPWA technologies are designed to support one-way communication for monitoring and are not appropriate for control. We present this work using an example of a water distribution network application, which we evaluate both through a co-simulator (modeling both physical and cyber subsystems) and testbed deployments. Our evaluation demonstrates full control stability, with up to 50% better packet delivery ratios and 80% less average end-to-end delays when compared to a state-of-the-art LPWA technology. We also evaluate our scheme against an idealised, wired, centralised, control architecture, and show that the controller maintains stability and the overshoots remain within bounds.

LoRaWAN is one of the leading Low Power Wide Area Network (LPWAN) architectures. It was originally designed for systems consisting of static sensor or Internet of Things (IoT) devices and static gateways. It was recently updated to introduce new features such as nano-second timestamps which open up applications to enable LoRaWAN to be adopted for mobile device tracking and localisation. In such mobile scenarios, devices could temporarily lose communication with the gateways because of interference from obstacles or deep fading, causing throughput reduction and delays in data transmission. To overcome this problem, we propose a new data forwarding scheme. Instead of holding the data until the next contact with gateways, devices can forward their data to nearby devices that have a higher probability of being in contact with gateways. We propose a new network metric called Real-Time Contact-Aware Expected Transmission Count (RCA-ETX) to model this contact probability in real-time. Without making any assumption on mobility models, this metric exploits data transmission delays to model complex device mobility. We also extend RCA-ETX with a throughput-optimal stochastic backpressure routing scheme and propose Real-Time Opportunistic Backpressure Collection (ROBC), a protocol to counter the stochastic behaviours resulting from the dynamics associated with mobility. To apply our approaches seamlessly to LoRaWAN-enabled devices, we further propose two new LaRaWAN classes, namely Modified Class-C and Queue-based Class-A. Both of them are compatible with LoRaWAN Class-A devices. Our data-driven experiments, based on the London bus network, show that our approaches can reduce data transmission delays up to 25% and provide a 53% throughput improvement in data transfer performance.

Hoisting equipment is core to many industrial systems and, therefore, their state of health significantly affects production lines and personnel safety; this is especially important in environments such as coal mines. The health of the hoisting system can be estimated by deploying energy harvesting wireless sensor nodes that monitor the drum surface stress. In this network of sensor devices, it is very costly to send highly sampled data as it causes radio congestion and consumes energy. However, from our experience of sensing hoist systems, we note that the data observed at the upper surface of the hoist are significantly more indicative of the state of health of the whole system, compared with data sensed at the lower surface. Therefore, we need to take advantage of this to optimize the communications of sensor nodes. However, scarce energy can be collected for these devices from the hoist itself, along with the prioritized Quality of Service (QoS) requirements (throughput, delay) of monitoring signals, raises important challenges for energy management. In this article, we use Lyapunov optimization techniques and propose an energy-neutral and QoS-aware protocol (EQP), including duty cycling and network scheduling to solve it. Extensive simulations show that the EQP helps sensor nodes realize consecutive monitoring, and achieve more than 38% utility gain compared with existing strategies.

Sensing systems incorporating unmanned aerial vehicles have the potential to enable a host of hitherto impractical monitoring applications using wireless sensors in remote and extreme environments. Their use as data collection and power delivery agents can overcome challenges such as poor communications reliability in difficult RF environments and maintenance in areas dangerous for human operatives. Aerial interaction with wireless sensors presents some interesting new challenges, including selecting or designing appropriate communications protocols that must account for unique practicalities like the effects of velocity and altitude. This poster presents a practical evaluation of the effects of altitude when collecting sensor data using an unmanned aerial vehicle. We show that for an otherwise disconnected link over a long distance (70m), by increasing altitude (5m) the link is created and its signal strength continues to improve over tens of metres. This has interesting implications for protocol design and optimal aerial route planning.

Low-Power Wide-Area Networks (LPWANs) are being successfully used for the monitoring of large-scale systems that are delay-tolerant and which have low-bandwidth requirements. The next step would be instrumenting these for the control of Cyber-Physical Systems (CPSs) distributed over large areas which require more bandwidth, bounded delays and higher reliability or at least more rigorous guarantees therein. This paper presents LPWA-MAC, a novel Low Power Wide-Area network MAC protocol, that ensures bounded end-to-end delays, high channel utility and supports many of the different traffic patterns and data-rates typical of CPS.