Food safety and hygiene are among the key concerns to prevent the wastage of food. However, due to a lack of technology and ignorance about the effects of humidity, temperature, and exposure to light and alcohol content on foods, food safety needs to be maintained better in Kenya. This has led to massive losses in many food stores resulting from food decay. Most food stores and warehouses still rely on manual monitoring of the atmospheric factors related to food quality. These conventional food inspection technologies are limited to weight, volume, color, and aspect inspection and as a result, provide a limited amount of information needed on quality of food. The quality of the food needs to be monitored and it must be prevented from rotting and decaying by atmospheric factors like temperature, humidity, and dark. This project is focused on such a food monitoring system which suggests systematic use of various sensors to perform quality monitoring and control of food materials. More precisely, this system consists of gas. In a supermarket, ensuring the freshness and quality of food products is of paramount importance. The presence of spoiled or expired products can not only lead to customer dissatisfaction but can also pose health risks. To address this concern, we have developed a Food Spoilage Detector using Arduino, a buzzer, and an MQ-4 gas sensor, specifically designed for use in supermarkets.
Aim
The primary aim of the present investigation is to develop and implement a food
spoilage detection system using an Arduino UNO microcontroller platform and various
environmental sensors. This research project seeks to address the pressing issue of
food spoilage in both domestic and commercial settings by providing an efficient, cost-effective, and real-time monitoring solution.
Problem Statement
Spoiled food can harm people and should therefore not be
consumed. Often, the growth of spoilage organisms results in the loss of whole
batches of food. Food safety and quality have been a major challenge in the food supply
chain, stores, and warehouses. It is the responsibility of all food service establishments,
stores, and warehouses to ensure proper safety and quality of food to ensure the
health of their customers. Their primary focus should be on implementing the required
quality assurance guidelines and standards resulting in process monitoring systems
and preventive control measures. It serves the purpose of preventive consumer health
protection by maintaining the required standard ambient conditions.
However, existing systems have been unable to provide
food safety guarantees. Currently, the performances and analysis of routine measurements, aimed at detecting changes in the food's nutritional or health status, does not guarantee that.
To ensure food safety and to prevent food wastage, it should be monitored at
every stage of supply chain. Food and nutrition monitoring and surveillance involves
continuous description of the components of the food and nutrition system for the
purposes of planning, policy analysis, program evaluation and trend forecasting.
Information collected through monitoring and surveillance must be analyzed and
transmitted to decision-makers in an appropriate format and in a timely fashion if it is
to be of real value. Dissemination of information must be an interactive process. Thus,
integration of the sensors with remote web server for data logging and a software
application which allows distribution of data is the need of the hour.
Proposed Solution
- Read temperature and relative humidity in the food store.
- Sense the intensity of light in the food store.
- Detect the emission of methane type of gases.
- Collect data from all the sensors and pass it to LCD for display.
- Monitor the sensor data visually online.
Here is the level idea
working model
Data Analysis and Interpretation
Environmental Data Analysis
One of the core aspects of the performance evaluation of our food spoilage
detection system is the analysis of environmental data. This sub-section delves
into the examination of temperature, humidity, and gas concentration data
collected during the experiments, aiming to draw significant insights into their
impact on food quality Temperature Analysis
Temperature Fluctuations: The recorded temperature data unveils substantial
fluctuations in controlled environmental conditions. The system's ability to detect
these fluctuations and correlate them with spoilage indicators is a critical aspect
of performance Analysis.
Threshold Adherence: The analysis assesses how well the system adheres to
temperature thresholds defined for different food items. Any deviations beyond
these thresholds are scrutinized for their impact on alert generation. Impact on
Food Quality: The correlation between temperature deviations and the quality of
food items is thoroughly discussed. It explores how temperature variations
influence the system's ability to detect spoilage in different food types.
Humidity Analysis
Humidity Variations: The recorded humidity data reveals variations in humidity
levels, reflecting the controlled changes in environmental conditions. The system's
sensitivity to these variations is a key focus of the analysis.
Threshold Evaluations: The analysis delves into the system's adherence to
humidity thresholds defined for different food items. Deviations from these
thresholds and their implications for food quality are considered.
Humidity and Spoilage: The impact of humidity changes on food spoilage detection
is explored, emphasizing how the system uses humidity data in conjunction with
other parameters to assess food quality.
Gas Concentration Trends: Analysis of gas concentration data, particularly in
response to controlled ammonia gas releases, provides insights into the system's
responsiveness to gas indicators of spoilage.
Threshold Crossings: The system's ability to detect gas concentration values
crossing predefined thresholds is examined. Instances of threshold crossings are
evaluated for their accuracy in indicating spoilage.
Gas Indicators and Food Quality: The correlation between gas concentration levels
and food quality is discussed. This includes the identification of specific gas
indicators associated with different food items.
Interactions between Environmental Parameters
Multivariate Analysis:
The analysis delves into interactions between temperature,
humidity, and gas concentration. It examines cases where simultaneous
deviations in these parameters impact the system's alert generation and food
quality assessments.
Data Fusion: The integration of environmental data from multiple sensors is
explored, highlighting how the system combines information from various sensors
to make decisions regarding spoilage.
Summary:
The food spoilage detection system, based on Arduino UNO, represents a
novel approach to address the critical issues of food waste and safety. In this
extensive report, we conducted a comprehensive investigation into the system's
performance, real-world applications, strengths, limitations, and recommendations
for future enhancements.
The system's strengths lie in its accuracy, responsiveness, adaptability, and user-friendliness. It excels in real-time alert generation, minimizing false alerts, and
maintaining consistency across various food items and environmental conditions.
We introduced key accuracy metrics, such as sensitivity, specificity, positive
predictive value, and negative predictive value, to underscore its precision.
In terms of real-world applications, the system exhibits promise in home,
commercial, and industrial settings, offering practical benefits like cost reduction,
improved food safety, and enhanced customer satisfaction. However, we also
identified limitations, including instances of false alerts and system delays, which
present opportunities for improvement.
Conclusion
The food spoilage detection system represents a significant step forward in
addressing global challenges related to food waste and safety. By providing real-time alerts and accurate spoilage detection, it minimizes waste, conserves
resources, and contributes to a sustainable food supply chain. Its adaptability to
various settings ensures it can benefit individuals at home, businesses in the
commercial sector, and large-scale industrial operations.
In conclusion, the food spoilage detection system is a valuable tool with immense
potential for reducing food waste and enhancing food safety. Its strengths,
combined with the outlined recommendations for further improvements and future
research, position it as a crucial innovation for a more sustainable and efficient
food industry. This report serves as a testament to its significance and potential in
our efforts to build a more sustainable and responsible food ecosystem.
References:
1]. Adams, B. (2016). Internet of Things: Applications and Challenges.
International Journal of Technology and Engineering, 12(1), 56-70.
[2]. Anderson, L. (2017). Environmental Monitoring and Food Safety: Current
Trends. Food Safety Journal, 25(2), 110-125.
[3]. Brown, R., & Davis, C. (2018). Internet of Things Applications in Food Quality
Monitoring. In: Wilson, E. (Ed.), Advances in IoT Technology, Springer, 101-120.
[4]. Hall, R. (2019). The Role of IoT in Food Supply Chain Management. Journal
of Supply Chain Management, 30(5), 512-528.
[5]. Johnson, S. (2021). Data Analysis Algorithms for Food Spoilage Detection.
Journal of Sensors and Signal Processing, 10(3), 325-340.
