AI-Driven Wastewater Irrigation Optimization System

Publication ID: 24-11856901_0001_PTD

Published: October 26, 2025

Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “AI-Driven Wastewater Irrigation Optimization System,” Published Technical Disclosure No. 24-11856901_0001_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856901_0001_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,856,901.

Background and Problem Solved

The original patent, 'Controlled irrigation process and system for land application of wastewater', has limitations in terms of optimizing wastewater treatment, biomass production, and energy consumption. The new invention addresses these limitations by introducing advanced sensors, machine learning algorithms, and dynamic protocols to ensure efficient and environmentally friendly wastewater irrigation.

Novelty and Inventive Step

The new invention introduces several novel features, including the use of real-time sensor data, machine learning algorithms, and dynamic protocols to optimize wastewater treatment, biomass production, and energy consumption. These features provide a significant improvement over the original patent, which relied on static measurements and manual adjustments.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include using different types of sensors, such as satellite-based sensors or drones, to collect data. The system could also be integrated with other wastewater treatment technologies, such as anaerobic digestion or membrane bioreactors, to create a hybrid system. Additionally, the machine learning algorithms could be trained on different datasets to optimize performance in various environmental conditions.

Potential Commercial Applications and Market

The Intelligent Wastewater Irrigation Optimization System has significant commercial potential in the wastewater treatment and agriculture industries. The system could be marketed to municipalities, agricultural companies, and wastewater treatment facilities, offering a cost-effective and environmentally friendly solution for wastewater management and biomass production.

CPC Classifications

Section	Class	Group
A	A01	A01G25/167
C	C02	C02F3/327

Section 103 Obviousness Analysis (PHOSITA)

▼

Field of Art

Agricultural and environmental engineering, specifically wastewater irrigation systems, focusing on soil moisture management and land application technologies

Person of Ordinary Skill (PHOSITA) Profile

An engineer with expertise in agricultural water management, soil science, irrigation control systems, and environmental engineering, typically holding a BS or MS degree with 3-5 years of practical experience in water resource management

Obviousness Rationale

A PHOSITA would recognize that the PTD's variations represent predictable technological improvements to the source patent's irrigation control methodology. The disclosed machine learning algorithms, real-time sensor integration, and dynamic scheduling are natural extensions of the original patent's core concept of soil water tension-based irrigation management. These variations apply standard engineering optimization techniques to enhance the existing wastewater irrigation control process.

Obvious Combinations & Variations

Source Patent Element

Soil water tension measurement for determining irrigation status

PTD Variation

Expanding sensor network to include rainfall intensity and evapotranspiration rate measurements

Obviousness Reasoning

Adding complementary environmental sensors is a known technique for improving irrigation precision, representing a predictable enhancement to existing measurement approaches

Source Patent Element

Static irrigation scheduling based on soil water tension

PTD Variation

Dynamic machine learning algorithm for predicting optimal irrigation schedules

Obviousness Reasoning

Applying machine learning to control systems is a standard engineering approach for optimizing complex environmental management processes

Source Patent Element

Manual adjustment of irrigation volume and duration

PTD Variation

Real-time automated adjustment based on multiple environmental and energy consumption parameters

Obviousness Reasoning

Implementing automated control systems with multiple input parameters is a routine design optimization in irrigation technology

Source Patent Element

Land application of wastewater for nutrient management

PTD Variation

Integrating energy consumption and pricing data into irrigation scheduling

Obviousness Reasoning

Incorporating economic optimization into technical systems is a predictable extension of existing control methodologies

Source Patent Element

Basic contaminant management in wastewater irrigation

PTD Variation

Establishing dynamic contaminant loading thresholds with real-time monitoring

Obviousness Reasoning

Enhancing environmental monitoring and establishing quantitative management thresholds represents an obvious improvement in environmental engineering practice

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856901, a Person Having Ordinary Skill In The Art would find the claimed variations in the present publication to be obvious extensions of existing wastewater irrigation control technologies. The disclosed improvements represent predictable combinations of known techniques in soil moisture management, sensor integration, and automated control systems, thereby rendering potential patent claims obvious under 35 U.S.C. § 103.

Original Patent Information

Patent Number	US 11,856,901
Title	Controlled irrigation process and system for land application of wastewater
Assignee(s)	GROUPE RAMO INC.