About this Research Topic
Artificial intelligence (AI) is a relatively new field of study that aims at solving problems mimicking the cognitive process used by humans. The constant increase of computers’ processing ability, along with the development of powerful algorithms and its distribution under open-source platforms have allowed the application of AI to many fields of science. The smart processing of information is changing sensors and building a new and revolutionary cross-disciplinary concept, AI-sensors. The integration of AI approaches including pattern analysis and classification algorithms with sensors can bridge the gap between data acquisition and analysis. To design and validate these monitoring systems, it is necessary to make use of AI techniques to deal with large amounts of heterogeneous data and extract useful information from them.
AI algorithms are becoming beneficial as substitute methods to conventional approaches or as components of incorporated systems. Nevertheless, AI-sensors are valuable only when data can be used by us, and understanding what the data means is a prerequisite for using them. AI data processing involves learning from the data, including how to analyze data appropriately, draw the right conclusions from the data, and recognize if the data has been misinterpreted. In this sense, new approaches involving the application of AI to sensors will be very valuable in order to increase the knowledge in this new field. Without doubt, AI is highly beneficial for the analytical chemist and in conjunction with novel concepts as Big Data and Internet of Things, AI-sensors will become something common for improving our life.
Areas of interest for this Research Topic could include, but are not limited to:
• AI for handling information from wearable sensors and biosensors for monitoring health.
• AI applied to sensors for food safety, quality control, and traceability.
Keywords: artificial intelligence, AI, food safety, health monitoring, machine learning, wearable sensors
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