Intuitive Auto Irrigation

Problems with Automated Irrigation

According to a study performed by the EPA in 2017, “Outdoor water use accounts for 30 percent of household use, yet can be much higher in drier parts of the country and in more water-intensive landscapes.”[1] Today, most irrigation systems still rely on outdated timer-based operation, resulting in inefficient water usage and overwatered plants.  The days of irrigation systems filling gutters with unused freshwater needs to come to an end; it is about time residential irrigation systems get updated with all-new technology.

Reducing Water-Waste Using Sensors

The Intuitive Auto-Irrigation (IAI) solution utilizes sensors placed near plants of interest. Through wireless communication, these sensor nodes relay readings of soil moisture and light level to a base station (the central hub) which accumulates all sensor and weather forecast data to determine when to trigger water delivery. Using the collection of data, the IAI system avoids unnecessary watering, effectively leading to a more sustainable method of general landscaping and residential gardening practices.

System Design

Central Hub: Wall-powered master node which receives real-time data from sensor nodes and weather forecast information to determine when to water. 

Key features include:

User interface: quick and easy configuration of the system 
Water delivery: precise control of irrigation using latching solenoid valves
Weather forecasting: prevention of irrigation based on precipitation chance
Data logging: data stored locally and on a database for easy access to users
Wireless communication: seamless transfer of data between sensor nodes and central hub over a 400ft minimum range makes setup less restricting
Sensor nodes: Multiple battery-powered subsystems featuring several sensors, each node is found at a watering subjects’ location. These nodes collect data and wirelessly transmit this data back to the Central Hub.
Equipped sensors: continuous monitoring of plant conditions using custom soil moisture sensors and light-level sensors.  

System Design

Soil Moisture Sensor Regression Modeling

In order to prevent unnecessary watering, the IAI system utilizes a custom soil moisture sensor at each node to determine the optimal time to water. For accurate soil moisture sensing, we use a power series regression model to accurately map soil moisture content to resistance across the sensor probes. Figure 1 shows this trend hold across two unique sensors and three sub-samples from a given location.

Soil Regression

Validation Testing and Results

Figure 2 shows data gathered during a 5-day field test that involved two sensor nodes and one master node. In the figure, the blue and green lines show the gravimetric water content for Node 4 and Node 5 respectively; the yellow and red lines show the ambient light level measured in lux for Node 4 and Node 5 respectively; and the vertical black lines indicate when water delivery was triggered. The test data showed the system watering when specific environmental conditions were met, proving its ability to provide irrigation only when plants 

Validation Testing


The Team

Sam Aiken (Data Logging and Forecast Lead), Brian Naranjo (User Interface & Water Delivery Lead),  Grant Skidmore (Project, Software, & Wireless Communications Lead), and Henry Tuckfield (Sensors & Power Systems Lead)