Relevant bibliographies by topics / Sensor data utilisation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Sensor data utilisation'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Sensor data utilisation"

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S, Sweta, and Balajee Maram. "Underwater Wireless Sensor Networks." JOIV : International Journal on Informatics Visualization 2, no. 1 (2018): 10. http://dx.doi.org/10.30630/joiv.2.1.99.

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There are a plenty of unexploited resources that lies underwater that covers almost 75% of the earth.In order to utilise them,the field of underwater wireless sensor networks (UWSN) is attracting the researchers to extend their thoughts in this field. The wireless sensor networks are heavy networks that consist of small low cost sensors that have a large amount of solving ability and energy resources which can be applicable in any type of irregular environments irrespective of changing conditions. Keeping in view of the real-time remote data transferring requirements, underwater acoustic sensor
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E. Sreedevi. "Efficient and Sustainable Utilizations of Sensor Networks with Minimal Traffic Using K-Medoid based Hybrid Clustering." Journal of Information Systems Engineering and Management 10, no. 37s (2025): 397–407. https://doi.org/10.52783/jisem.v10i37s.6430.

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The network traffic is one of the significant research issues in current communication industries due to people are passing bulk and unwanted data to transmit from one network segment to another network segments. Efficient and sustainable utilisation of sensor networks necessitates minimal traffic within the networked sensors (WSNs). These networks comprise multiple sensor nodes that are interconnected, and their optimal performance is achieved through the avoidance of congestion, low energy consumption, elimination of duplicate information transmission, and minimal data transfers to the sink.
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Isikdag, U., K. Sahin, and S. Cansiz. "A MACHINE LEARNING APPROACH ON OCCUPANT NUMBER PREDICTION FOR INDOOR SPACES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 275–81. http://dx.doi.org/10.5194/isprs-archives-xlii-4-275-2018.

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<p><strong>Abstract.</strong> The knowledge about the occupancy of an indoor space can serve to various domains ranging from emergency response to energy efficiency in buildings. The literature in the field presents various methods for occupancy detection. Data gathered for occupancy detection, can also be used to predict the number of occupants at a certain indoor space and time. The aim of this research was to determine the number of occupants in an indoor space, through the utilisation of information acquired from a set of sensors and machine learning techniques. The senso
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Chmielewski, Mariusz, and Michał Nowotarski. "Wearable sensor-based data analysis for neurological disease symptoms evaluation utilising quantitative approach." MATEC Web of Conferences 210 (2018): 05015. http://dx.doi.org/10.1051/matecconf/201821005015.

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The paper describes implementation of an analytical method and conclusions of novel approach to clinical trials monitoring and evaluation. Based on clinical trials observations a set of requirements for validating symptoms of neurological diseases have been formulated, concentrating on the ones which can be registered using wearable sensors. The constructed tool utilizes conventional surveying methods supplemented with biomedical sensor for neurological symptoms recognition and intensity evaluation. Developed mobile system is aimed at clinical trials assistance utilising sensor-based state eva
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Malihi, S., L. Potseluyko, A. Mathew, et al. "Review of multimodal data and their applications for road maintenance." Smart Construction 1, no. 2 (2024): 2960–033. https://doi.org/10.55092/sc20240010.

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The application of multimodal data in road maintenance has attracted considerable attention due to its potential to enhance decision-making processes and improve infrastructure resilience. This paper provides a comprehensive review of the utilisation of various modalities of multimodal data, including LiDAR, RGB images, thermal images, ground-penetrating radar (GPR), text, audio, and some others for road maintenance tasks. The research methodology thoroughly examines existing literature, categorising data modalities and analysing their respective applications. The paper discusses the integrati
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Chughtai, Omer, Nasreen Badruddin, Maaz Rehan, and Abid Khan. "Congestion Detection and Alleviation in Multihop Wireless Sensor Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9243019.

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Multiple traffic flows in a dense environment of a mono-sink wireless sensor network (WSN) experience congestion that leads to excessive energy consumption and severe packet loss. To address this problem, a Congestion Detection and Alleviation (CDA) mechanism has been proposed. CDA exploits the features and the characteristics of the sensor nodes and the wireless links between them to detect and alleviate node- and link-level congestion. Node-level congestion is detected by examining the buffer utilisation and the interval between the consecutive data packets. However, link-level congestion is
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Balamurugan, P., Marimuthu Karuppiah, A. Mummoorthy, A. M. Viswabharathi, and R. Niranchana. "Consistent and effective energy utilisation of node model for securing data in wireless sensor networks." International Journal of Grid and Utility Computing 9, no. 3 (2018): 220. http://dx.doi.org/10.1504/ijguc.2018.093978.

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Balamurugan, P., Marimuthu Karuppiah, A. Mummoorthy, A. M. Viswabharathi, and R. Niranchana. "Consistent and effective energy utilisation of node model for securing data in wireless sensor networks." International Journal of Grid and Utility Computing 9, no. 3 (2018): 220. http://dx.doi.org/10.1504/ijguc.2018.10015145.

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Ernst, Sebastian, Leszek Kotulski, Adam Sędziwy, and Igor Wojnicki. "Graph-Based Computational Methods for Efficient Management and Energy Conservation in Smart Cities." Energies 16, no. 7 (2023): 3252. http://dx.doi.org/10.3390/en16073252.

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Computational methods play a significant role in reducing energy consumption in cities. Many different sensor networks (e.g., traffic intensity sensors, intelligent cameras, air quality monitoring systems) generate data that can be useful for both efficient management (including planning) and reducing energy usage. Street lighting is one of the most significant contributors to urban power consumption. This paper presents a summary of recent attempts to use computational methods to reduce energy usage by lighting systems, with special focus on graph-based methods. Such algorithms require all th
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Kohli, Priya. "An Improved Method Of Cluster Head Selection Using Machine Learning In Wsn." Mathematical Statistician and Engineering Applications 70, no. 2 (2021): 1400–1408. http://dx.doi.org/10.17762/msea.v70i2.2332.

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Wireless Sensor Networks (WSNs) are comprised of numerous small, low-cost, and energy-limited sensor nodes that gather information from their immediate surroundings and relay it to a sink node. The utilisation of cluster-based routing protocols has been widely employed in Wireless Sensor Networks (WSNs) with the aim of enhancing network efficacy and extending network longevity. In the context of Wireless Sensor Networks (WSNs) that are cluster-based, the network is partitioned into clusters, with each cluster being assigned a Cluster Head (CH) responsible for data aggregation and forwarding to
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Dissertations / Theses on the topic "Sensor data utilisation"

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Fabre, Léa. "Contributions and Opportunities of Wi-Fi Data to Improve Transport Demand Knowledge / Utilisation de données Wi-Fi, quels apports pour la connaissance de la demande de transport?" Electronic Thesis or Diss., Lyon 2, 2024. http://www.theses.fr/2024LYO20011.

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La mobilité joue un rôle clé dans les paysages urbains, en particulier, les transports en commun sont essentiels au bon fonctionnement des villes. Par conséquent, il est nécessaire de planifier les systèmes de transport en commun afin de leur garantir un fonctionnement efficace. Pour cela, il est important d'avoir une bonne connaissance de la demande de transport en commun, d'autant plus dans un monde en constante évolution.Actuellement, nous observons une forte croissance démographique mondiale ainsi qu'un important étalement urbain, deux facteurs qui sont les principales causes de l'augmenta
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Book chapters on the topic "Sensor data utilisation"

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Hall, Jack, Bubaker Shakmak, Amin Al-Habaibeh, and Eiman Kanjo. "The Analysis of Sensory Data from Smart Office Environment Towards the Development of an Intelligent System." In Springer Proceedings in Energy. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30960-1_17.

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AbstractWith the increase in energy prices and the drive to reduce carbon emission, this paper presents an investigation of the use of smart office environments to monitor and evaluate the sustainability and behaviour of employees and the utilisation of space and resources. This paper presents analysis of data in an office environment in a company in Derby city to attempt to understand the behaviour of employees, pattern of work, power consumption and performance of heating and air-conditioning systems. Data from occupancy, room temperature, CO2, humidity, lighting, air temperature, windows status are all collected and analysed. The data also included external environmental conditions. The results indicate some correlation between CO2 levels and the number of employees. They also show correlation between outside and inside environmental conditions. In addition, the utilisation of space was also monitored, and the results demonstrate low utilisation during most days, this was due to Covid-19 and to working from home and off-site patterns. However, the data is found useful to inform future decisions about the actual space needed for normal working conditions.
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Mourkousis, Georgios, Matthaios Protonotarios, Chrysostomos Antoniou, et al. "EURMARS: An Advanced Surveillance Platform to Improve the European Multiauthority Border Security Efficiency and Cooperation." In Security Informatics and Law Enforcement. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62083-6_31.

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AbstractEuropean maritime border management is a complex and multifaceted task. EURMARS innovates border surveillance in Europe by addressing the main challenges of irregular migration attempts, smuggling, trafficking, as well as management of search and rescue operations and oil spill observation and monitoring in parallel with the coordination and cooperation among different authorities and agencies at the national and EU levels. EURMARS implements and intends to validate a 24/7 surveillance platform with the following characteristics: (i) provision for the integration of existing and future data sources and services; (ii) utilisation and clustering of high-altitude technology, satellite imagery, UAVs, and ground-based sensors into a joint surveillance capability to provide continuous complementary data; (iii) innovative coupling of sensors data with data fusion, AI analytics, risk assessment, and alarming functionality; (iv) flexible interoperable surveillance platform with multiauthority cooperation capabilities and verified easy-to-integrate potential for next-generation platforms and systems; and (v) performance benchmark platform to ensure acceptability by all stakeholders, including extensive technical and user acceptance tests and ethical and legal impact assessments.
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Armeni, Iro, Deepika Raghu, and Catherine De Wolf. "Artificial Intelligence for Predicting Reuse Patterns." In Circular Economy and Sustainability. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-39675-5_4.

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AbstractArtificial intelligence, and specifically the subfields of computer vision and machine learning, has become a topic with great potential for predicting reuse patterns in the built environment. With sensors that collect visual data becoming more readily available, new opportunities are created to digitalise the built environment by applying technologies from these fields. Applications include exploring the design space, monitoring construction progress, and improving building performance during operation. Using these applications to increase circularity in the built environment requires information about in-use building products and their attributes (e.g. type, material, size, geometry, condition, etc.). This information is a starting point for many downstream circular processes and a core component of circular databases, which can enable designers, constructors, and facility managers to follow a circular paradigm. Many advancements have been made in academia and industry towards extracting such information from visual and other building data, e.g. for the downstream processes of predicting material reusability or automating the maintenance of building facades. This chapter presents efforts on this front and highlights the gaps in adopting and utilising these technologies for the circular built environment, including challenges in developing comprehensive systems for their deployment and in robustly evaluating them. It also discusses business and organisational considerations with respect to adoption, utilisation, and development of the technologies in the circular context.
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Mikulecky Peter. "Intelligent Environments Approaches Applied in Water Management." In Ambient Intelligence and Smart Environments. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-530-2-27.

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Recently, we are in the époque of sophisticated Ambient Intelligence (AmI) applications, mainly based on utilisation of wide sensor networks together with advanced AmI approaches. If we concentrate on environmental (that is, open space or outdoor) applications, there is just a few of them, although basically focused on environmental monitoring, that enable more functionalities than just collecting environmentally related data and passing them to further elaboration. In our paper we intend to go further on with the ideas how environmentally oriented wireless sensor networks used in “large-scale” throughout the open natural environment could be enhanced using some recent AmI approaches in order to be beneficial in preventing primarily environmentally related problems, if not even disasters. We focus our attention on the area of water management with accent on two critical water related problems: floods management and drought-stricken periods. We suggest a concept of an approach how to solve a particular water management problem in Czech Republic using large-scale ambient intelligence approach enhancing thus wireless sensor network focused on environmental monitoring.
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Delsi Robinsha, S., B. Amutha, D. Vanusha, and R. Prithviraj. "Leveraging Intelligent Transportation Systems for Predictive Roadway Maintenance." In Urban Mobility and Challenges of Intelligent Transportation Systems. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7984-4.ch027.

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Intelligent Transportation Systems (ITS) are a significant development in contemporary infrastructure that have the potential to revolutionise the maintenance of roadways through the application of predictive analytics. In order to improve the safety, efficiency, and durability of road networks, this chapter investigates the possibility of integrating intelligent transportation systems (ITS) with predictive maintenance tactics. Through the utilisation of real-time data collecting, advanced sensor technologies, and machine learning algorithms, Intelligent Transportation Systems (ITS) are able to recognise patterns and forecast the deterioration of roadways before it becomes critically important. This proactive strategy makes it possible to make timely interventions, which in turn reduces the frequency of emergency repairs and the cost of such repairs, minimises disturbances to traffic, and improves the overall experience of travellers on roads. Several components of Intelligent Transportation Systems (ITS) are discussed in this chapter.
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Sri-Ganeshan, Muhuntha, and Peter Cameron. "Remote Monitoring in Telehealth: Advancements, Feasibility and Implications." In A Comprehensive Overview of Telemedicine [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1004661.

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Over the past several decades, telehealth has evolved within various medical fields, gaining momentum with sequential technological advancements. The development of remote monitoring specifically expands the function of telehealth by facilitating the ongoing review of patients remotely. Through leveraging of technologies such as wearable sensors, mobile apps, and implantable devices, remote patient monitoring (RPM) enables the collection of biometric data for clinical decision-making. The utilisation of decision-making algorithms in addition to this can flag patient deterioration prompting for a clinician review. This narrative review summarises disease-specific applications, patient and clinician perspectives, and potential future acute care applications, highlighting RPM as a promising tool that, when combined with telehealth, could revolutionise healthcare delivery in the near future.
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Ojha, Mritunjaykumar, Abhijeet Das, Sonali Patil, Ashish Pandey, Chinmay Kulkarni, and Anurag Nalawade. "Real-Time Environmental Monitoring With IoE Systems." In Advances in Computational Intelligence and Robotics. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-7367-5.ch020.

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The introduction of real-time environmental monitoring, which is facilitated by Internet of Everything (IoE) technology, has substantially enhanced the capacity to collect, evaluate, and respond to environmental data. Real-time data on environmental factors, including noise, temperature, humidity, and water and air quality, is collected by IoE systems. This is accomplished through the utilisation of a network of communication channels, devices, and sensors. In order to guarantee prompt responses and valuable insights, we employ sophisticated analytics and state-of-the-art machine learning algorithms to further process this data. By facilitating more informed and efficient decision-making, the Internet of Everything (IoE) has the potential to enhance environmental monitoring, public health, and sustainable development. The complexity of designing and implementing IoE systems to monitor environmental conditions in real time is the focus of this study. It investigates the fundamental technologies, as well as the diverse applications and obstacles that are linked to these systems.
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Sivakumar, R., B. Prabadevi, G. Velvizhi, et al. "Internet of Things and Machine Learning Applications for Smart Precision Agriculture." In Ubiquitous Computing [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97679.

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Agriculture forms the major part of our Indian economy. In the current world, agriculture and irrigation are the essential and foremost sectors. It is a mandatory need to apply information and communication technology in our agricultural industries to aid agriculturalists and farmers to improve vice all stages of crop cultivation and post-harvest. It helps to enhance the country’s G.D.P. Agriculture needs to be assisted by modern automation to produce the maximum yield. The recent development in technology has a significant impact on agriculture. The evolutions of Machine Learning (ML) and the Internet of Things (IoT) have supported researchers to implement this automation in agriculture to support farmers. ML allows farmers to improve yield make use of effective land utilisation, the fruitfulness of the soil, level of water, mineral insufficiencies control pest, trim development and horticulture. Application of remote sensors like temperature, humidity, soil moisture, water level sensors and pH value will provide an idea to on active farming, which will show accuracy as well as practical agriculture to deal with challenges in the field. This advancement could empower agricultural management systems to handle farm data in an orchestrated manner and increase the agribusiness by formulating effective strategies. This paper highlights contribute to an overview of the modern technologies deployed to agriculture and suggests an outline of the current and potential applications, and discusses the challenges and possible solutions and implementations. Besides, it elucidates the problems, specific potential solutions, and future directions for the agriculture sector using Machine Learning and the Internet of things.
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Sarkar, Nurul I., Anita Xiao-min Kuang, Kashif Nisar, and Angela Amphawan. "Hospital Environment Scenarios using WLAN over OPNET Simulation Tool." In Healthcare Administration. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6339-8.ch040.

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For the past ten years, heterogeneous networks wired and wireless had tended to integrate seamlessly, offering effective and reliable service for medical operations. One of the problems encountered by network practitioners is the seamless integration of network components into healthcare delivery. As a multiplexing hospital model, the implementation certainly presents some challenges. The major technical and performance issues involve are as following. The operating parameters should keep aligned to the Quality of Service (QoS) requirement throughout simulation. Bandwidth utilisation of wireless networking is a challenging issue for real-time multimedia transmission. IEEE 802.11 provides relatively lower data rate than wired networks, thus the developer tends to adopt a more compromised solution: either reduce the file size or compress the image packets. Communication performance that varies constantly with the impact of signal strength, traffic load and interference. As stated radio signal senses as a curve and attenuates greatly while metallic object and microwave exist within the active range. To ensure devices do not interfere with other electronic equipments (e.g. heart monitors), assert wireless spectrum has to be managed appropriately. This research paper aims to develop a generic hospital network scenarios using Wireless Local Area Network (WLAN) over OPNET Simulation, to evaluate the performance of the integrated network scenario for Intensive Care Units (ICU). This research makes use of computer simulation and discusses various aspects of the network design, so as to discover the performance behaviour pertaining to effect of traffic type, traffic load and network size. In the ICU scenario, the performance of video conference degrades with network size, thus, a QoS-enabled device is recommended to reduce the packet delay and data loss. IEEE 802.11a suits in hospital environment because it mitigates interference on the 2.4GHz band where most wireless devices operate. Experiment examines the effect of signal strength in WLAN. It is convinced that -88dBm is the best signal strength threshold. Although 802.11a generates slightly lower throughput than 802.11g, this issues can be addressed by placing more APs in the service area. It is convinced that 802.11a suits the hospital environments, because it mitigates interference on the popular 2.4GHz band where most wireless devices operate. It is important for medical devices which require future upgrade and Bluetooth deployment.
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Conference papers on the topic "Sensor data utilisation"

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Bolettieri, Simone, and Raffaele Bruno. "QoS-Aware Data Management Mechanisms for Optimal Resource Utilisation in Crowd-Assisted Shared Sensor Networks." In 2020 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2020. http://dx.doi.org/10.1109/smartcomp50058.2020.00031.

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Simandjuntak, S., N. Bausch, A. Farrar, et al. "iWindCr Wireless Sensor System for Corrosion Detection and Monitoring of Offshore Wind Turbine Structures." In International Conference on Marine Engineering and Technology Oman. IMarEST, 2019. http://dx.doi.org/10.24868/icmet.oman.2019.023.

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The iWindCr system, designed and developed to comprise miniaturised corrosion sensors to form a Wireless Sensor Network (WSN), has been piloted in one of the 116 offshore wind turbines located in the south region of the UK. The iWindCr system that was equipped with low power-low current sensor interface incorporating the Open Circuit Potential (OCP) and Zero Resistance Ammeter (ZRA) electrochemical technique analysis and the Internet of Things (IoT) was employed to detect and/or monitor electrochemical activities in relation to corrosion on the surface of the M72 stud, part of the monopole (MP
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Bulander, Rebecca, Bernhard Kölmel, and Marcel Rath. "Development of a Procedure for the Processing of Raw Sensor Data from Smart Devices for Utilisation in Process Mining." In 20th International Conference on Smart Business Technologies. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0012122700003552.

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Sayed, Mohamed, Ahmed Sabaa, Ahmed Samir, Mohamed Mokhtar, Ahmed Medhat, and Ahmed El-Wakil. "Effective Utilisation of Underbalanced Perforation with Electrical Submersible Pump's Boost Oil Production of Mature Oil Field in Western Desert of Egypt: Case Study." In International Petroleum Technology Conference. IPTC, 2023. http://dx.doi.org/10.2523/iptc-22793-ea.

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Abstract Conventionally, the transition from completion to production often requires the well to be killed immediately after perforation is completed, thus exposing the formation to potentially damaging killing fluid. To obtain a perforation tunnel with maximum productivity, this transition requires an optimal clean-up and removal of the perforation damages. Underbalance perforation through Tubing Conveyed Perforating (TCP) system is one of the best practices to ensure less damage to the perforation tunnels (perforating skin) leading to increased well productivity. However, it is very challeng
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Bances P, Enrique, Vedant Dalvi, Urs Schneider, and Thomas Bauernhansl. "Deploying a Transformer-based Model in Microservices Architecture: An Approach for Real-Time Body Pose Classification." In 13th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications. AHFE International, 2025. https://doi.org/10.54941/ahfe1005921.

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Real-time body pose classification is essential in preventing injuries caused by repetitive strain or poor ergonomics. In industrial environments, ensuring worker safety often requires monitoring the poses of multiple individuals performing different tasks. However, analysing the movements of many workers simultaneously presents computational challenges, potentially impacting accuracy and latency. In this context, microservices architecture offers significant advantages for enabling individual application functionalities to operate independently. Also, this architecture allows systems to scale
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Ucchiello, Mattia Francesco. "The Importance of Data Visualisation in Natural Capital Conservation Scenario: Enhancing Decision-making Processes Through User Analysis, Personalisation and Co-design." In 8th International Visual Methods Conference. AIJR Publisher, 2024. http://dx.doi.org/10.21467/proceedings.168.18.

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The conservation of Natural Capital emerges as a critical challenge for future generations, requiring the integration of nature and technology for effective monitoring and management. Leveraging tools like IT sensors, software, and AI, particularly evident in Agriculture 4.0, has yielded promising outcomes across various fields such as environmental conservation. However, to harness the full potential of the data collected, efficient presentation and comprehension mechanisms are essential, considering diverse stakeholders, especially end-users like scientists and policymakers. This necessitate
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Song, Seung Woo, Chungkuk Jin, and Do Kyun Kim. "A Novel Approach for Ship Digital Twin Optimisation: Principal Component Analysis-Driven Distortion Base Mode Selection and Utilisation." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-124226.

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Abstract This study aims to improve the efficiency of distortion base mode selection using Principal Component Analysis (PCA) and enhance structural response estimation techniques for digital twin applications in the maritime structures. Real-time determination of loads on a structure is essential for digitalisation in the maritime sector. Methods such as modal superposition and inverse finite element methods have been investigated to calculate loads at arbitrary points from a limited number of sensors. The objective of this study is to estimate loads by using a conversion matrix constructed b
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Olatoye, Oluwafemi, and Andrew Arewa. "Exploring the Effect of Wearable Digital Devices (WDDs) on Adverse Occupational Health and Safety Practices of High-Risk Workers." In Human Interaction and Emerging Technologies (IHIET-FS 2025): Future Systems and Artificial Intelligence Applications. AHFE International, 2025. https://doi.org/10.54941/ahfe1005951.

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Globally, workers in high-risk industries are often exposed to hazards with devastating effects, leading to occupational health infections, injuries, and fatalities. Despite the advent of Wearable Digital Devices (WDDs), contemporary research examining their influence vis-à-vis high-risk industry workers' health and safety practices is inadequate. Aim: The study explores the influence of wearable digital devices on managing adverse occupational health and safety practices among workers in high-risk industries. Research question: Does the use of wearable digital devices influence safety practic
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Olatoye, Oluwafemi, and Andrew Arewa. "Exploring the Effect of Wearable Digital Devices (WDDs) on Adverse Occupational Health and Safety Practices of High-Risk Workers." In Human Interaction and Emerging Technologies (IHIET-FS 2025): Future Systems and Artificial Intelligence Applications. AHFE International, 2025. https://doi.org/10.54941/ahfe10059725951.

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Globally, workers in high-risk industries are often exposed to hazards with devastating effects, leading to occupational health infections, injuries, and fatalities. Despite the advent of Wearable Digital Devices (WDDs), contemporary research examining their influence vis-à-vis high-risk industry workers' health and safety practices is inadequate. Aim: The study explores the influence of wearable digital devices on managing adverse occupational health and safety practices among workers in high-risk industries. Research question: Does the use of wearable digital devices influence safety practic
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Hendawy, Mostafa Mohamed, Albert Kwasi G. Boohene, Omar Labib, Kenneth Vullum-Bruer, and Yves Minier. "Flowline Sustainable Operations through Monitoring and Digitalisation – Ærfugl Project Case Study." In Offshore Technology Conference. OTC, 2023. http://dx.doi.org/10.4043/32576-ms.

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Abstract Unlocking the value of product data for the subsea industry is essential to improving efficiency and sustainability from early engagement to fabrication, installation and throughout the product life cycle. Unlike standard flowlines managed with temperature sensors on trees which provide limited information to the operator, Ærfugl Project implemented distributed flowline temperature monitoring, to allow effective mitigation against hydrate formation utilising active heating technology. The case study was a collaborative effort between the project's subsea umbilical, riser and flowline
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