Design of remote data collection devices for social impact indicators of products in developing countries. (2021)

• Record Type: Journal Article
• Authors: Stringham, Bryan J.; Mattson, Christopher A.
• Is Part Of: Development engineering. Volume 6(2021)
• Publication Date: 2021
• Subjects: Engineering for global development -- Design for the developing world -- Social impact -- Sensor systems -- Internet of things -- Development canvas; Technical assistance -- Periodicals; Economic development -- Periodicals; Engineering -- Social aspects -- Periodicals; 338.9105
• DOI: 10.1016/j.deveng.2021.100062
• Languages: English
• ISSNs: 2352-7285

Abstract

Abstract: Social impact indicators provide one effective way to measure the social impacts of products in developing countries and ensure that engineering design is producing positive impacts on individuals. Remote data collection devices enable the use of sensors to collect user data required to calculate social impact indicators remotely, continuously, and potentially less expensively than other methods that require direct interaction with users. However, many key decisions and questions must be considered during the development and use of such devices to avoid risk of failure. To provide a systematic way for researchers and engineers to consider critical device development questions, the parts of device development and use can be decomposed into Data Identification, Device Design, and Device Deployment. This paper discusses the key decisions within each part of development along with critical questions, common options, and considerations that should be addressed during each part of device development, thus increasing the likelihood of success. A sensor development canvas outlining the key decisions is also provided as a design tool to easily identify deficiencies in the device during development. Considering these critical questions while developing and deploying data collection devices can help researchers and engineers successfully collect social impact indicator data that may be used to ensure engineered products are producing desired positive impacts on individuals.