IoT Based Agriculture System

Inspiration

Helping farmers by ensuring high yields, profitability, and protection of the environment. The approach of using IoT technology to ensure optimum application of resources to achieve high crop yields and reduce operational costs is called precision agriculture

What it does

When the IOT based agriculture monitoring system starts it checks the water level, humidity and moisture level. It sends SMS alert on the phone about the levels. Sensors sense the level of water if it goes down, it automatically starts the water pump.

How we built it

The basic building blocks of an IoT System are Sensors, Processors, and applications. The sensors are interfaced with Microcontroller, data from the sensor is displayed on the mobile app of the user. A mobile app provides an access to continuous data from sensors and accordingly helps the farmer to take action to fulfill the requirements.

Challenges we ran into

THREE MAJOR OBSTACLES FOR IOTS IN AGRICULTURE

Poor Internet Connectivity in Farms.
High Hardware Costs
Disrupted Connectivity to the Cloud

Accomplishments that we're proud of

Efficiency:- IOT-enabled agriculture allows farmers to monitor their products and conditions in real time. Reduced resources:- Plenty of IoT solutions are focused on optimizing the use of resources. Agility:- One of the benefits of using IoT in agriculture is the increased agility of the processes.

What we learned

In this project, we have learned how to make a smart agriculture system that will help us to monitor different parameters that are necessary for the proper growth of the plants. And how to connect physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. Various, Sensors that are used in Project. What are the applications of that sensors? How the Sensors actually work in real world.

What's next for IoT Based Agriculture System

The next proposed system focuses on automatic irrigation of water and plant disease detection. It uses machine learning algorithms to accurately predict adequate water required by the fields and automatic pest identification based on the requirements of the farmland.