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Abstract

This paper explores the transformative journey of electronic perception systems, focusing on the shift from conventional technologies to neuromorphic paradigms. Electronic perception encompasses artificial systems such as electronic noses, electronic tongues, and electronic vision, designed to mimic human sensory capabilities. Traditional systems rely on sensor arrays and classical data processing methods to interpret sensory information. However, recent advancements in neuromorphic engineering—emulating the brain's neural architecture and functionality—offer significant improvements in efficiency and adaptability. Neuromorphic sensing utilizes event-driven sensors and spiking neural networks (SNNs) to process information in real-time, while neuromorphic computing leverages specialized hardware for efficient data processing. These innovations promise substantial gains in power efficiency, speed, and dynamic learning capabilities, making them ideal for applications in healthcare, environmental monitoring, food safety, and autonomous systems. We delve into the specific technologies underpinning neuromorphic electronic noses, tongues, and vision systems, highlighting their advantages and challenges. By integrating neuromorphic processors with sensory arrays, these systems achieve real-time processing, enhanced adaptability, and reduced power consumption. This paper underscores the potential of neuromorphic paradigms to revolutionize electronic perception, paving the way for more intelligent and efficient sensory technologies

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