Integrated and Personalised Risk Management in the Sensing Enterprise

Lazaro, Oscar; Moyano, Agustín; Uriarte, Mikel; González, Alicia Blanco; Meneu, Teresa; Fernández-Llatas, Juan Carlos; Traver, Vicente; Molina, Beatriz Lucas; Palau, Carlos E.; López, O.; Sanchez, Etxahun; Ros, Saioa; Moreno, Antonio Vallecillo; González, María; Palazón, José Antonio; Sepulcre, Miguel; Gozálvez, Javier; Collantes, Luis; Prieto, Gonzalo

doi:10.5772/50275

Cited by 8 publications

(7 citation statements)

References 22 publications

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“…Initial attempts to develop an OSH risk monitoring system in the SWE were made within the project FASyS. The project's findings have led to a rationale for personalised risk management in the so-called sensing enterprise, [91] and to a proposal of reference architecture of an ICT-based platform aimed at the operation of wireless networks that connect mobile sensors in industrial environments. [92] In reference to the idea of personalised risk management, one should also mention attempts at personalised assessment of OSH risks related to the development of ORCA (Occupational Risk Calculator), a software tool which allows for quantified risk assessment for individual workers or jobs.…”

Section: Ict Applications Devoted To Osh Risk Assessmentmentioning

confidence: 99%

Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the Internet of Things technologies

Podgórski

Majchrzycka

Dąbrowska

et al. 2016

International Journal of Occupational Safety and Ergonomics

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Recent developments in domains of ambient intelligence (AmI), Internet of Things, cyber-physical systems (CPS), ubiquitous/pervasive computing, etc., have led to numerous attempts to apply ICT solutions in the occupational safety and health (OSH) area. A literature review reveals a wide range of examples of smart materials, smart personal protective equipment and other AmI applications that have been developed to improve workers' safety and health. Because the use of these solutions modifies work methods, increases complexity of production processes and introduces high dynamism into thus created smart working environments (SWE), a new conceptual framework for dynamic OSH management in SWE is called for. A proposed framework is based on a new paradigm of OSH risk management consisting of real-time risk assessment and the capacity to monitor the risk level of each worker individually. A rationale for context-based reasoning in SWE and a respective model of the SWE-dedicated CPS are also proposed.

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Section: Ict Applications Devoted To Osh Risk Assessmentmentioning

confidence: 99%

Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the Internet of Things technologies

Podgórski

Majchrzycka

Dąbrowska

et al. 2016

International Journal of Occupational Safety and Ergonomics

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“…In the manufacturing area, there have been several advances in hazard risk management and their approach to the preservation of worker's safety and health has been highly improved, by developing new work equipment features and definition of more secure tasks [9].…”

Section: Research Connection With Cyber-physical Systemsmentioning

confidence: 99%

“…A big trend that has been emerging in this area is the definition of a sensing and smart factory, which uses information from a network of physical sensors and virtual databases to make real-time risk assessments [9], which has been extensively overviewed for the construction industry [10]. These sensors can also be used to monitor and track the assembly line, by using real-time information to guide the manual assembly process [11].…”

Section: Research Connection With Cyber-physical Systemsmentioning

confidence: 99%

Low Cost Inertial Measurement Unit for Motion Capture in Biomedical Applications

Lourenço¹,

Martins²,

Almeida³

et al. 2016

Technological Innovation for Cyber-Physical Systems

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A low-cost inertial measurement unit has been developed for accurate motion capture, allowing real-time spatial position registration (linear and angular) of the user's whole-body. For this, we implemented a dedicated circuit for 9 degrees of freedom motion sensors, composed of an accelerometer, gyroscope and a magnetometer. We also applied signal processing and data fusion algorithms to prevent the inherent drift of the position signal. This drift is known to exist during the sensor integration process and the implemented algorithms showed promising results. This system is meant to be used in two specific biomedical applications. The first one is linked to the development of a low-cost system for gait analysis of the whole-body, which can be used in home-based rehabilitation systems. The second application is related to the realtime analysis of working postures and the identification of ergonomic risk factors for musculoskeletal disorders.

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“…As stated by (Lazaro et al, 2012), "The Sensing enterprise concept leverages the power of sensor networks and decentralised intelligence to perform analysis and decision making both in synchronised real and virtual worlds." The usage of sensor networks and decentralised decision making systems creates a change in the boundaries of the enterprise, in terms of where an enterprise gathers and collects data for its decision-making processes.…”

Section: Sensing Enterprisementioning

confidence: 99%