We did a project to build a cloud system for storing and managing agrotechnology data. This system helps people monitor and take care of their ecosystems, like gardens and parks. Here's how it works:
1. Connecting Devices to the Cloud (IoT)
The project uses the "Internet of Things" (IoT) to create a network of smart devices that monitor the environment. It's like giving the garden a nervous system! Small, low-power sensors are placed throughout the area, acting like tiny weather stations. These sensors constantly gather crucial information about the microclimate, such as:
- Temperature: How hot or cold it is in different spots.
- Soil Moisture: How much water is in the ground, making sure plants aren't too thirsty or too soggy.
- Light Intensity: How much sunlight reaches different areas, which is important for plant growth.
Here's what makes up the IoT system:
- Tiny Sensors: These are small devices that measure things in the environment.
- Gateways: These devices gather information from the sensors and send it to the cloud.
- Cloud Platform: We use Amazon Web Services (AWS) to store the information and do calculations with it.
2. Sending Information Safely
To send information from the sensors to the cloud, we use special ways of communicating:
- MQTT
This is a simple way for small devices to send messages. It's good for saving energy. - HTTP
This is a common way for computers to talk to each other. We use it to send information from the gateways to the cloud.
3. Using Amazon's Cloud (AWS)
We use AWS because it has many tools to help us build a strong and reliable system.
Here are the main AWS tools we use:
- AWS IoT Core: This helps us connect the sensors to the cloud and keep the information safe.
- Amazon Timestream: This is a special database for storing lots of data with timestamps, like the information from our sensors. We use it to keep track of all the sensor readings and to analyze the data to give people helpful advice.
- Amazon S3: This is where we store extra copies of the data, just in case.
- Amazon RDS: We use this to store information about users and their devices.
- AWS Lambda: This helps us process the data and send alerts.
- Amazon API Gateway: This lets other applications talk to our system.
In Conclusion
The cloud system I helped build for the project makes it easy to collect, store, and understand information from the sensors. Amazon Timestream helps us store and analyze this information efficiently. Using AWS gives us the flexibility to grow as the project grows. We're planning to add even more features, like using machine learning to predict how ecosystems will change in the future.
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