Artificial Intelligence (AI) is the simulation of human intelligence in machines programmed to think like humans and mimic their actions. The term can also apply to any machine that exhibits traits associated with a human mind, such as learning and problem-solving.
In the landscape industry, AI shifts emphasis for landscape contractors to achieve irrigation management accuracy and efficiencies not seen before. This is becoming more important to customers as water prices increase.
Companies that adapt AI first will win more jobs and need more employees.
In landscape irrigation, AI applications are part of the broader movement toward precision agriculture and smart landscaping. These applications are designed to increase efficiency and conservation by leveraging data, machine learning and automation.
For landscape irrigation, AI applications can now compute and respond in milliseconds to the three critical questions in landscape irrigation scheduling.
How much?
Starting with how much should I water, an AI application gathers and processes environmental data from multiple sources to understand how much water is currently in the soil available for plants. The calculations occur each hour, specifically for each plant.
When weather data tracking includes evapotranspiration and rainfall, the AI application determines how much water went into the ground, how much ran off and the soil soak rate. It then uses this information to determine how much water is without over or underwatering.
In addition, using predictive analytics for weather for irrigation schedules in the future provides exceptional value. Why water a total amount today if it will rain tomorrow or the next day? How much of the water that falls will be usable and how to incorporate this into an accurate irrigation schedule is available today through AI in irrigation.
When?
The next question is when during the day or night should the irrigation take place? Most water managers agree to provide the answer at the first light of day. However, the best answer is when evapotranspiration is the lowest, at a time before the plant reaches a permanent wilting point, and how this correlates to other plants in the zone. Very complex decision-making for a human, but with AI and all the data available to the application recorded on an hourly basis, the answer is easy to calculate.
How?
The last question is how to water. Knowing how you are watering the plant (spray head, drip emitter, bubbler, etc.) combined with soil data information allows AI to determine the perfect watering program. This uses the concept of soil and soak when necessary and provides exact instructions on watering a given plant best considering precipitation and flow rates, soil soak rate, slope and allowed surface accumulation.
Thanks to detailed algorithms, AI systems can now perform mammoth computing tasks much faster and more efficiently than human minds, helping to make significant strides in research and development areas worldwide. A human cannot perform the calculations AI can use to determine or adjust a watering schedule.
This includes:
- Use and selection from multiple sources of data.
- Using cross-correlation of large data sets.
- Hourly analysis of data sets.
- An optimal schedule that is predictive of future weather events.
These technologies are continually evolving, with new advancements appearing as the field of AI grows. Both commercial and residential landscape operations are beginning to adopt these smart technologies to conserve water, reduce costs and maintain healthier landscapes.