Social Impact Assessment of HealthyAIR Tool for Real-Time Detection of Pollution Risk

Antonia Moreno Cano, Rafael Romón Sagredo, Rocío García-Carrión and Begonya Garcia-Zapirain
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Antonia Moreno Cano: eVIDA Research Group, University of Deusto, Avd. de las Universidades, 24, 48007 Bilbao, Bizkaia, Spain
Rafael Romón Sagredo: eVIDA Research Group, University of Deusto, Avd. de las Universidades, 24, 48007 Bilbao, Bizkaia, Spain
Rocío García-Carrión: Faculty of Psychology & Education, University of Deusto, Ikerbasque, Basque Foundation for Science, Avd. de las Universidades, 24, 48007 Bilbao, Bizkaia, Spain
Begonya Garcia-Zapirain: eVIDA Research Group, University of Deusto, Avd. de las Universidades, 24, 48007 Bilbao, Bizkaia, Spain

Sustainability, 2020, vol. 12, issue 23, 1-21

Abstract: Background: HealthyAIR is a tool that detects pollution risk in real life. The target population is people with cardiorespiratory complications who are especially susceptible to the current COVID-19. The goal is to empower people by controlling air pollution everywhere to minimize the risk of having a seizure. Methods: We measured the social impact of the HealthyAIR tool using a Likert scale survey with two groups: professionals (engineers/healthcare) and end-users. We assessed the data in accordance with the indicators for social impact defined for the Key Impact Pathways introduced by the European Commission for Horizon Europe, and the criteria of the Social Impact Open Repository (SIOR). Results: Professionals highlight the fact that they “totally agree” (33.33%) and “agree” (26.67%) that HealthyAIR could help authorities improve their health prevention policies and programs. Users considered the tool to be “very useful” (38.46%) and “quite useful” (42.31%), which denotes its necessity. Conclusions: professionals and end users see HealthyAIR as a great preventative tool, with the former seeing it as a way to avoid seizures in their patients who, in this COVID-19 era, are particularly sensitive to any cardiorespiratory health problem. However, users suggest improving the user’s manual to make it more understandable.

Keywords: social impact; COVID-19; big data; embedded system; sensors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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