Big Data Analytics for Air Quality Monitoring at a Logistics Shipping Base via Autonomous Wireless Sensor Network Technologies
| Autor: | Judith Molka-Danielsen, Peter Sarafin, Veronika Olesnanikova, Robert Zalman, Per Engelseth |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
Supply chain management business.industry media_common.quotation_subject Big data 02 engineering and technology Computer security computer.software_genre 030210 environmental & occupational health Occupational safety and health Visualization 03 medical and health sciences 0302 clinical medicine Indoor air quality Risk analysis (engineering) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Quality (business) business Wireless sensor network Air quality index computer media_common |
| Zdroj: | ES |
| DOI: | 10.1109/es.2017.14 |
| Popis: | The indoor air quality in industrial workplace buildings, e.g. air temperature, humidity and levels of carbon dioxide (CO2), play a critical role in the perceived levels of workers' comfort and in reported medical health. CO2 can act as an oxygen displacer, and in confined spaces humans can have, for example, reactions of dizziness, increased heart rate and blood pressure, headaches, and in more serious cases loss of consciousness. Specialized organizations can be brought in to monitor the work environment for limited periods. However, new low cost wireless sensor network (WSN) technologies offer potential for more continuous and autonomous assessment of industrial workplace air quality. Central to effective decision making is the data analytics approach and visualization of what is potentially, big data (BD) in monitoring the air quality in industrial workplaces. This paper presents a case study that monitors air quality that is collected with WSN technologies. We discuss the potential BD problems. The case trials are from two workshops that are part of a large on-shore logistics base a regional shipping industry in Norway. This small case study demonstrates a monitoring and visualization approach for facilitating BD in decision making for health and safety in the shipping industry. We also identify other potential applications of WSN technologies and visualization of BD in the workplace environments; for example, for monitoring of other substances for worker safety in high risk industries and for quality of goods in supply chain management. |
| Databáze: | OpenAIRE |
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