Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 29 | Compact Electronic Nose for Food Identification and Freshness Monitoring |
Haotian Li Torres Zhang Zhenyu Zhang |
Shengkun Cui | ||
| # Problem Food freshness is usually evaluated using expiration dates, visual inspection, or human smell. These methods are subjective and may not detect early spoilage. As food ripens or decomposes, it releases volatile compounds such as alcohols, ammonia, sulfur-containing gases, and other VOCs. A single low-cost gas sensor cannot reliably identify food because it normally responds to several different gases. However, an array of sensors with different sensitivities can generate a unique response pattern for each food and freshness condition. Many existing low-cost electronic nose projects use prebuilt sensor modules and passive air sampling. Their results are often affected by airflow, temperature, humidity, and sensor placement. Our project aims to improve repeatability through a custom PCB and a controlled sampling system. # Solution We propose a compact electronic nose that identifies predefined foods and estimates whether they are fresh or spoiled. A small diaphragm pump will draw gas from a food container into a sealed sensing chamber. Four gas sensors mounted on a custom PCB will respond to different components of the food odor. Their signals will be filtered, digitized, and processed by an STM32 microcontroller. The STM32 will compare the sensor responses with a clean-air baseline and generate an odor fingerprint. A lightweight classification algorithm will use this fingerprint to predict the food type and freshness state. After the result is displayed, the system will introduce filtered air to clean the chamber before the next measurement. # Solution Components Gas-Sensor Subsystem The system will use four raw gas sensors rather than prebuilt sensor modules. The proposed sensors are: TGS2602 for general VOCs, ammonia, and sulfur-containing odors; TGS2620 for ethanol and other organic vapors; MQ137 for ammonia and organic amines; MQ136 for hydrogen sulfide and sulfur-containing vapors. The sensors will be placed near one edge of the PCB so that they can extend into the sensing chamber. The remaining electronics will remain outside the chamber to reduce the influence of circuit heat. Each sensor will have its own load resistor, voltage-scaling circuit, and low-pass filter. A TLV9004 quad operational amplifier will buffer the four signals before they are measured by the ADC. # Data-Acquisition and Processing Subsystem The main controller will be an STM32F411RCT6 mounted directly on the PCB. It will control the sampling sequence, collect sensor measurements, calculate odor features, run the classifier, and present the result. An ADS1115 four-channel ADC will digitize the four gas-sensor signals. A separate SHT31 temperature and humidity sensor will record environmental conditions so that the STM32 can compensate for their effect on the gas sensors. The classifier will first be trained on a computer using experimental data. The final model will then be stored on the STM32 so that classification can be performed without a connected computer. # Air-Sampling Subsystem The airflow system will include: A sealed sensing chamber; A food-sample container; A miniature 5 V diaphragm pump; A three-way solenoid valve; Sample tubing; A clean-air filter. The valve will switch between the food sample and filtered ambient air. The pump will draw the selected gas through the sensing chamber. The STM32 will automatically perform the following sequence: Purge the chamber with filtered air. Record the clean-air baseline. Switch the valve to the food sample. collect the sensor responses. classify the food and freshness. display the result. purge the chamber again. Power and Pump-Control Subsystem The system will be powered through USB-C. The 5 V input will directly supply the gas-sensor heaters, pump, and solenoid valve. A 3.3 V regulator will supply the STM32, ADC, environmental sensor, and analog circuits. The pump and valve will be controlled using MOSFET driver circuits. Flyback diodes and bulk capacitors will protect the PCB and reduce electrical noise when the pump or valve switches. The PCB will also include an SWD programming connector, a start button, status LEDs, and USB serial communication for data collection and debugging. # User Interface Subsystem The user will place a food sample in the container and press the start button. Status LEDs will indicate whether the device is purging, sampling, processing, or ready. The final result can be shown using a small display or sent to a computer through USB. It will include the predicted food type and freshness condition. # Criterion for Success The project will be considered successful if: The team designs, fabricates, and solders a custom PCB containing the raw gas sensors, STM32, ADC, analog circuits, power regulation, and pump-control circuits. The system automatically completes the baseline, sampling, classification, and purge sequence after the user presses the start button. Repeated measurements of the same food produce similar sensor-response patterns. The prototype can distinguish at least two predefined foods, initially apples and bananas. The prototype can distinguish fresh and spoiled samples with at least 80% accuracy. The system produces a result within five minutes and successfully returns the sensors close to their clean-air baseline before the next measurement. |
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