The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy.
Sensors (Basel). 2017 Jun 20;17(6):1453. doi: 10.3390/s17061453.
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.
新一代的移动感应方法在测试速度、控制、低成本、易于操作和数据管理方面相对于传统平台具有显著优势，并且只需要最小的设备和用户参与。新型感应技术与智能手机的结合使得许多重要应用（包括医疗诊断、环境监测和食品安全分析）的智能手机实验室平台得以发展。本文综述了基于智能手机的食品诊断技术领域的最新进展和发展，重点介绍了增强智能手机感应能力的定制模块。这些设备通常包括多个组件，如探测器、样品处理器、一次性芯片、电池和软件，它们与商业智能手机集成在一起。开发这些系统最重要的方面之一是将这些组件集成到一个紧凑且轻便的平台上，该平台需要最小的功率。迄今为止，研究人员已经展示了几种有前途的方法，采用了各种感应技术和设备配置。我们旨在根据检测策略进行系统分类，对优缺点进行批判性讨论。我们还将分析扩展到越来越多的物联网（IoT）市场中的食品扫描设备，展示了这个领域确实很有前途，因为研究成果很快就被新的初创公司所利用。
