Novel Gas Sensor Signal Acquisition Method: Amplifying Sensor Signals and Enabling Efficient Gas Identification.

Enhancing sensor sensitivity and gas identification capabilities is essential for the broad application of gas sensors. Developing efficient transducing methods for sensors can be applied to a wide range of sensors. However, developing such methods for resistive sensors remains challenging.

On-Chip Annealing Using Embedded Micro-Heater for Highly Sensitive and Selective Gas Detection.

The demand for gas sensing systems that enable fast and precise gas recognition is growing rapidly. However, substantial challenges arise from the complex fabrication process of sensor arrays, time-consuming data transmission to an external processor, and high energy consumption in multi-stage data processing. In this study, a gas sensing system using on-chip annealing for fast and power-efficient gas detection is proposed.

Energy Efficient Artificial Olfactory System with Integrated Sensing and Computing Capabilities for Food Spoilage Detection.

Artificial olfactory systems (AOSs) that mimic biological olfactory systems are of great interest. However, most existing AOSs suffer from high energy consumption levels and latency issues due to data conversion and transmission. In this work, an energy- and area-efficient AOS based on near-sensor computing is proposed.

Transducer-Aware Hydroxy-Rich-Surface Indium Oxide Gas Sensor for Low-Power and High-Sensitivity NO Gas Sensing.

Low-power metal oxide (MOX)-based gas sensors are widely applied in edge devices. To reduce power consumption, nanostructured MOX-based sensors that detect gas at low temperatures have been reported. However, the fabrication process of these sensors is difficult for mass production, and these sensors are lack uniformity and reliability.