Mechanical Engineering, Agricultural and Biosystems Engineering, Food Science and Human Nutrition, Virtual Reality Applications Center, Ames Laboratory
Journal or Book Title
In this review, we discuss the role of sensor analytics point solutions (SNAPS), a reduced complexity machine-assisted decision support tool. We summarize the approaches used for mobile phone-based chemical/biological sensors, including general hardware and software requirements for signal transduction and acquisition. We introduce SNAPS, part of a platform approach to converge sensor data and analytics. The platform is designed to consist of a portfolio of modular tools which may lend itself to dynamic composability by enabling context-specific selection of relevant units, resulting in case-based working modules. SNAPS is an element of this platform where data analytics, statistical characterization and algorithms may be delivered to the data either via embedded systems in devices, or sourced, in near real-time, from mist, fog or cloud computing resources. Convergence of the physical systems with the cyber components paves the path for SNAPS to progress to higher levels of artificial reasoning tools (ART) and emerge as data-informed decision support, as a service for general societal needs. Proof of concept examples of SNAPS are demonstrated both for quantitative data and qualitative data, each operated using a mobile device (smartphone or tablet) for data acquisition and analytics. We discuss the challenges and opportunities for SNAPS, centered around the value to users/stakeholders and the key performance indicators users may find helpful, for these types of machine-assisted tools.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
McLamore, Eric S.; Datta, Shoumen Palit Austin; Morgan, Victoria; Cavallaro, Nicholas; Kiker, Greg; Jenkins, Daniel M.; Rong, Yue; Gomes, Carmen; Claussen, Jonathan C.; Vanegas, Diana; and Alocilja, Evangelyn C., "SNAPS: Sensor Analytics Point Solutions for Detection and Decision Support Systems" (2019). Mechanical Engineering Publications. 467.