Capacity of Broadband Body-to-Body Channels Between Firefighters Wearing Textile SIW Antennas

Castel, Thijs; Torre, Patrick Van; Vallozzi, Luigi; Marinova, Marina; Joseph, Wout; Oestges, Claude; Rogier, Hendrik

doi:10.1109/tap.2016.2535488

Cited by 18 publications

(4 citation statements)

References 42 publications

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“…Textile‐based communication and tracking systems are critical for rescue workers and firefighters working in a harsh environment. [ 168 ] Vallozi et al [ 169 ] proposed a GPS patch antenna based on conductive textile for rescue workers. They integrated the antenna into a protective garment and evaluated the antenna performance by taking real‐time measurements.…”

Section: Types Of Wearable Textronicsmentioning

confidence: 99%

Textronics—A Review of Textile‐Based Wearable Electronics

et al. 2021

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Textronics contribute a significant part of Internet‐of‐Things (IoT), which empowers added functionalities by connecting smart clothing in a secure way for diverse applications. For the development of flexible and stretchable textile‐based electronics, a conductive material (yarn, fabric, etc.) must be used, and fabrication techniques play a vital role that significantly influences electronic textiles’ properties. Textile‐based sensors, electrodes, and other devices seem to be the favorite choice for continuous wearable monitoring due to their low cost, flexibility, and ease of embedding. Integrating smart capabilities into textiles provides substantial benefits in the fields of healthcare, sports, automobile, and military. These developments have a profound influence on the Fourth Industrial Revolution (4IR). This Review presents an in‐depth study of the current state of the art in the area of textile‐based electronics. The design, development, and evaluation techniques are discussed. Certain limitations and research gaps are also addressed regarding this emerging field. Critically, this Review is more application focused and indicates how the recent developments in electronic textiles will soon impact our lives. As these areas have typically been neglected in previous reviews, additional knowledge to the existing literature is provided by bridging the gap between the academic research and commercialization of wearable Textronics.

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Section: Types Of Wearable Textronicsmentioning

confidence: 99%

Textronics—A Review of Textile‐Based Wearable Electronics

et al. 2021

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“…Many techniques report on the use of sensors to monitor firefighters' health and warn them of any threats to their safety. Several safety areas are being considered including tracking indoor location of first responders [13]- [15], physiological monitoring [16]- [18], and communication [19], [20]. There have also been substantial advancements in the research and development of intelligent threat assessment systems for firefighters.…”

Section: Background and Related Workmentioning

confidence: 99%

An Autoregressive Exogenous Neural Network to Model Fire Behavior via a Naïve Bayes Filter

et al. 2020

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This work presents an artificial neural network-based linearly regressive technique for the prediction of a temperature rise event caused by a fire in enclosed building environments. The method predicts temperature range in a burning compartment based on the historic fire behavior data modelled via a neural network algorithm. The approach further extends the method by transforming the regression outcome as actionable information for firefighters via a self-organising feature map (SOM) fire-stageclustering algorithm which categorises the predicted temperature range to provide warnings of any imminent and catastrophic temperature variations. The methodology implements a linear regression artificial neural model to model and predicts catastrophic temperature variations that are a threat to fire-and-rescue personnel in enclosed burning compartments via a ceiling gas-layer temperature acting as an exogenous variable. Based on the predicted temperature window, the SOM classifier maps the output in distinct clusters while isolating spurious prediction spikes and categorising the output to various self-organising threat/warning levels. The model was trained on temperature data captured with pole-mounted sensors in controlled fire training exercises. Tests carried out in actual fire-settings showed the capability of the SOM classifier to generate evacuation warnings for forecasted temperatures exceeding 300 C in 5-30 seconds ahead of the occurrences. Tests on these short-term and long-term prediction ranged from 78.31% to 96.27% in accuracy whereas the SOM classifier generated an overall accuracy of 76.92% to 100%. The techniques also showed a high resilience against both false-positives and false-negatives. INDEX TERMS Artificial neural networks, fire behaviour modelling, linear regression, self-organising feature maps.

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“…Moreover, the antenna orientation and position is highly uncertain. The use of multiple antennas, deployed at suitable locations, can significantly improve the reliability and capacity of the channel through MIMO techniques, such as beam forming [12], diversity [16], [26] and spatial multiplexing [27].…”

Section: Leveraging Multi-antenna Processing Techniquesmentioning

confidence: 99%

Recent advances in materials and technologies for body-centric and IoT antenna systems

Agneessens¹,

Rogier²

2017

2017 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-A

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In the recent decade, we have witnessed a revolution in wireless communication systems. In this contribution, some novel materials and technologies for the development of dedicated antennas systems for body-centric communication and the Internet of Things are presented. In particular, the use of textile and cork materials as antenna substrates, combined with conducting electro-textiles or very thin copper-on-polyimide layers. Next, we focus on antenna topologies that yield highly stable radiation characteristics owing to their excellent body-antenna isolation. Therefore, we implement wide band cavity-backed slot antennas in substrate integrated waveguide technology. This enables the design of highly efficient active textile antenna systems where electronic circuitry and energy harvesters are deployed in very close proximity of the radiating parts of the antenna. Finally, we demonstrate how these systems may leverage multi-antenna processing techniques to increase throughput and robustness of the wireless channel.

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Capacity of Broadband Body-to-Body Channels Between Firefighters Wearing Textile SIW Antennas

Cited by 18 publications

References 42 publications

Textronics—A Review of Textile‐Based Wearable Electronics

Textronics—A Review of Textile‐Based Wearable Electronics

An Autoregressive Exogenous Neural Network to Model Fire Behavior via a Naïve Bayes Filter

Recent advances in materials and technologies for body-centric and IoT antenna systems

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