Are you interested in how technology can help solve the issue of food insecurity? An artificial intelligence of things (AIOT) technology-based food security system may be the answer. This system leverages AI, cloud computing, Python tools, and IoT sensors such as humidity sensors to collect and analyze data on crop health, storage conditions, and food distribution, generating real-time insights that inform policy decisions, improve agricultural productivity, and reduce food waste. In this blog post, we’ll dive into the details of how an AIOT-based food security system works and the role that cloud, Python, and humidity sensors play in making it possible. Join us as we explore the intersection of technology, cloud computing, IoT, and food security.

What is AIoT Technology?

AIoT technology is a combination of Artificial Intelligence (AI) and Internet of Things (IoT) technology. It enables the devices to communicate with each other and share data. AIoT technology can help to analyze the data and provide insights that can be used to improve the efficiency and effectiveness of the system.

Humidity Sensor: –

The DHT11 is a digital humidity and temperature sensor that can be used to measure the relative humidity and temperature of the surrounding environment. It is a low-cost sensor that is easy to use and can provide accurate readings in a variety of applications. The DHT11 sensor contains a calibrated digital signal output with a temperature and humidity sensor complex. It has a single-bus digital interface and can measure temperatures from 0°C to 50°C with an accuracy of ±2°C, and humidity levels from 20% to 90% with an accuracy of ±5%.

The DHT11 sensor can be used in a variety of applications, including:

Indoor climate control: The DHT11 sensor can be used in indoor climate control systems to measure the temperature and humidity levels and adjust the heating or cooling systems accordingly.

Agriculture: The DHT11 sensor can be used in agriculture to monitor the humidity levels in soil or air, helping to optimize crop growth and yield.

Food storage: The DHT11 sensor can be used to monitor the humidity levels in food storage areas to ensure that the food remains fresh and does not spoil.

Medical applications: The DHT11 sensor can be used in medical applications to monitor the temperature and humidity levels in hospitals, laboratories, and research facilities.

Overall, the DHT11 sensor is a versatile and affordable option for measuring humidity and temperature in a wide range of applications.

Here are the step-by-step instructions to implement the food security system using ESP8266, DHT11, and Firebase:

Step 1. Hardware setup:

A.Connect the DHT11 sensor to the ESP8266 board

B. Configure the ESP8266 board to read the temperature and humidity data from the DHT11 sensor

Code:-

C. Write the code to read the data from the sensor and send it to Firebase Cloud.

Code:-

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Step 2. Firebase Cloud Setup:

This is a cloud-based platform provided by Google that enables developers to build real-time web and mobile applications. Firebase Cloud can be used to store and retrieve data in real time of DHT11 values to monitor Food quality parameters.

  1. Create a Firebase account at https://firebase.google.com/.
  2. Create a new project in Firebase.
  3. In the project settings, enable the Realtime Database.

Firebase database configuration:

  1. In the Firebase console, create a new database.
  2. Configure the security rules to allow read/write access to the database.
  3. Note down the database URL and authentication credentials.

Data transmission:

  1. Install the Firebase API on the ESP8266 board.
  2. Write the code to transmit the temperature and humidity data to Firebase Cloud.
  3. Use the Firebase API to connect to the Firebase database using the database URL and authentication credentials.

Follow this blog to configure firebase with esp8266- Link

Code:-

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Step 3. Data Collection:

Data collection is an essential part of the food security system as it helps to monitor the storage conditions of the food. The data collected can be used to analyze the trends and patterns in the storage conditions, which can be used to improve the system’s effectiveness.

Python Code for Data Collection

Here is an example code snippet that shows how to read data from the Firebase and write it to a CSV file using Python.

Code:-

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Step 5. Machine Learning

Machine learning is a subset of AI that enables the systems to learn from the data and make predictions. It can be used to analyze the collected data and provide insights that can be used to improve the system’s performance. Machine learning can help to predict the storage conditions of the food and provide alerts when the conditions go beyond a certain threshold.

Code to predict Values:-

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Step 4. Automation

Automation is an essential part of the food security system as it helps to monitor food storage conditions continuously. The system can be automated to provide alerts when the storage conditions go beyond a certain threshold. It can help to prevent spoilage and wastage, which can lead to food insecurity.

Code for Automation:-

Conclusion:

In conclusion, the storage food security system based on AIOT technology, Firebase, data collection, data analysis, and automation, using the ESP8266 microcontroller, is an efficient way to monitor and optimize food storage conditions. The system can be customized to meet the requirements of different storage environments and can help ensure food security in developing countries. With the availability of affordable hardware and cloud computing solutions, such systems are becoming more accessible, and their adoption can have a significant impact on food security.