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Automation is a key technology for a sustainable and secure meat sector in the future, both in terms of productivity and work environment. New robotic technologies, such as the so-called “meat factory cell,” (MFC) aim to contribute to this goal, but they require new “smart” tools that provide sensor feedback, which enable robots to perform complex tasks. This article presents one such tool: the smart knife, which gives real-time feedback on its contact status with meat, as well as cutting depth. The tool and the system are described, and its operation evidenced via electromagnetic (EM) simulation using the Ansys High-Frequency Structure Simulator. Furthermore, the performance of the knife is validated using pork loin meat: in the worst case, knife is shown to have an error of 1.78% for contact detection, and a mean error of 7.66 mm (±1.45 mm) for depth detection. This article also presents brief discussion regarding eventual use of the knife as part of the MFC control system, in addition to future work to be performed.

Goal: This paper reports a novel electromagnetic sensor technique for real-time noninvasive monitoring of blood lactate in human subjects. Methods: The technique was demonstrated on 34 participants who undertook a cycling regime, with rest period before and after, to produce a rising and falling lactate response curve. Sensors attached to the arm and legs of participants gathered spectral data, blood samples were measured using a Lactate Pro V2; temperature and heart rate data was also collected. Results: Pointwise mutual information and neural networks are used to produce a predictive model. The model shows a good correlation ${\rm{(R\,= \,0.78)}}$ between the standard invasive and novel noninvasive electromagnetic wave based blood lactate measurements, with an error of 13.4% in the range of 0–12 mmol/L. Conclusion: The work demonstrates that electromagnetic wave sensors are capable of determining blood lactate level without the need for invasive blood sampling. Significance: Measurement of blood metabolites, such as blood lactate, in real-time and noninvasively in hospital environments will reduce the risk of infection, increase the frequency of measurement and ensure timely intervention only when necessary. In sports, such tools will enhance training of athletes, and enable more effecting training regimes to be prescribed.

This paper reports a novel electromagnetic sensor technique for real-time noninvasive monitoring of blood lactate in human subjects.The technique was demonstrated on 34 participants who undertook a cycling regime, with rest period before and after, to produce a rising and falling lactate response curve. Sensors attached to the arm and legs of participants gathered spectral data, blood samples were measured using a Lactate Pro V2; temperature and heart rate data was also collected.Pointwise mutual information and neural networks are used to produce a predictive model. The model shows a good correlation between the standard invasive and novel noninvasive electromagnetic wave based blood lactate measurements, with an error of 13.4% in the range of 0-12 mmol/L.The work demonstrates that electromagnetic wave sensors are capable of determining blood lactate level without the need for invasive blood sampling.Measurement of blood metabolites, such as blood lactate, in real-time and noninvasively in hospital environments will reduce the risk of infection, increase the frequency of measurement and ensure timely intervention only when necessary. In sports, such tools will enhance training of athletes, and enable more effecting training regimes to be prescribed.

There is a growing demand for non-invasive point of care devices to monitor metabolites in blood such as lactate. In hospital environments, having such tools would reduce the risk of infection, increase the frequency of measurement and ensure timely intervention only when necessary. In sports situations, such tools will enhance training of athletes, and enable more effecting training regimes to be prescribed. This work demonstrates the use of novel electromagnetic wave lactate sensors on cyclists, 34 in total, in a controlled environment. Sensors attached to the arm and legs of participants gathered spectral data, blood samples were measured using a Lactate Pro V2, as well as temperature and heart rate data being collected. Using pairwise mutual information and neural networks, a predictive model is shown to give a good correlation (R = 0.78) between the standard invasive and novel non-invasive microwave based blood lactate measurements, with an error of 13.4% in the range of 0–12 mmol/L.

Since 2008, the Department of Infrastructure on the Isle of Man, located within the British Isles, has been investigating the use of polymer curb units in order to minimize workforce injury. With little current work detailing the experiences of early adopters of these new curb units, this work presents the findings from seven case studies on the Isle of Man. In addition, experimental testing is undertaken in order to determine the suitability of polymer curbs in a variety of real-world situations.

Urban emissions have been considered an issue in the UK since as early as the 13th century, when the use of coal was banned in London because of the damaging effects to human health. Despite air quality improving in the last century, the establishment of legislative controls and limits, in addition to developments in sensing technology are helping to reduce further the pollutant levels present in the air. Technological advances, such as the emergence of Wireless Sensor Networks (WSNs), and complex computer based tools may allow for both the capturing and analysis of data in order to address the issue of emissions from road transportation systems. This work delves into the possibility of remotely obtaining real-time emissions data at the vehicle level using a combination of WSNs and Geographical Information Systems (GISs). The paper adopts a design science research methodology, discussing the rationale for the novel approach taken and presenting empirical measurements from a vehicle to demonstrate the principle of the work.

This paper reports on testing of the performance of SmartLife® e-textile material. In particular, the response of the integrated conductive pathways at microwave frequencies in the region of 9 kHz to 6 GHz is investigated for both biomedical sensing and signal transmission purposes. The experimental results confirm the viability of exciting the e-textile material at ISM microwave frequencies at mW powers for the purposes of wearable non-invasive sensing. Custom made flexible microwave sensors suitable for integration into smart e-textile fabric were tested in their ability to perform real-time body parameters monitoring, in particular the level and composition of perspiration. Gradual change in both the resonant frequency peak and amplitude was recorded in the 2-3 GHz frequency range with increased volume of fluid (50-350 μl) when in contact with a 5×8 mm2 sensor. This fabric with built-in textile sensors could serve as a platform for “high-tech designer outfits” for an advanced healthcare approach where real-time data on patient condition is transmitted wirelessly for immediate processing and corrective action if necessary. The novel sensor reported here was recently patented under milestone UK patent application number GB 2500000.

A Geographical Information System (GIS) is a computer system designed to integrate, store, edit, analyse, share and display geographically referenced data. A wireless sensor network (WSN) is a wireless network of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions. This paper presents the integration of these two technologies to create a system able to detect measure and transmit information regarding the presence and quantities of internal combustion derived pollution and the geographical location in real time with the aim of creating pollution maps in urban environments.