{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T04:45:53Z","timestamp":1774500353359,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T00:00:00Z","timestamp":1497916800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies.<\/jats:p>","DOI":"10.3390\/s17061453","type":"journal-article","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T10:15:38Z","timestamp":1497953738000},"page":"1453","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":286,"title":["Smartphone-Based Food Diagnostic Technologies: A Review"],"prefix":"10.3390","volume":"17","author":[{"given":"Giovanni","family":"Rateni","sequence":"first","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy"}]},{"given":"Paolo","family":"Dario","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7432-5033","authenticated-orcid":false,"given":"Filippo","family":"Cavallo","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,20]]},"reference":[{"key":"ref_1","unstructured":"(2017, February 01). 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