A mobile-based wireless sensor network to eliminate ineffecient methods of irrigation
H20 smart is a wireless sensor network-based smartphone application to regulate the inefficient methods of irrigation. Agriculture uses 85% of available freshwater resources worldwide, which will continue to dominate water consumption because of population growth and increased food demand.
There is an urgent need to create strategies based on science and technology for sustainable use of water, including technical, agronomic, managerial, and institutional improvements.
Freshwater is used by an average Australian each year.
Available freshwater is used for agriculture.
Surface irrigation is when water is applied to the soil surface and distributed by gravity.
It is by far the most common type of irrigation in the world, and it has remained virtually unchanged.
In Queensland, Daniel owns a number of farm fields, including wheat and barley farms. Irrigation methods currently in use waste a significant amount of water. Daniel is looking for a cost-effective way to irrigate his fields based on their wet basis.
• Uncontrolled distribution of water due tosurface irrigation.
• Lack of data on temperature and moistureto implement efficient irrigation.
The experience should be personal to farm owners with different soil types. The app should have a degree of customisation while still being consistent across multiple platforms.
Regardless of the device or platform they use, CEOs and farmers should be able to access core H2O smart functionalities at any time and from anywhere.
The system should be easy to understand, intuitive to operate, and accommodating to users who use screen readers or alternative input devices.
I wanted to create a friendly, approachable, and easy-to-use experience that focused on a real problem. The ultimate goal of the app was to eliminate water wastage through automation.
The onboarding process only included the regulations required to connect the wireless sensor network.
The app was connected to wireless sensors that provided real-time data such as the quantity of soil moisture or the amount of irrigation needed to reach a desired level of water in the soil.
For temperature and soil moisture, I implemented several graph types based on their attribute profiles. Each graph's units were customised to meet the needs of the user.
The dashboard's design was based on the notion of scalability. To collect and visualise data, the app can be linked with various sensor networks.
The sprinkler control panel was designed to activate the sprinklers when the soil moisture content falls below the required level.
The approach was pleasant, playful, and approachable, with a focus on straightforward communication.
The app lets the user turn on the sprinklers as soon as the soil is below the recommended wet basis.