Surveying & Inspecting AI Agents
Agentic AI is redefining how industries interact with their environments by introducing autonomous systems capable of perceiving, deciding, and acting independently—bringing intelligence, efficiency, and adaptability to diverse domains like agriculture, energy, aquaculture, and mining.
In agriculture, these intelligent agents leverage drones, robotics, and sensor networks to monitor soil conditions, weather, pests, and crop health in real time. With this data, they make autonomous decisions about irrigation, fertilization, and pest control—maximizing yield while minimizing waste and environmental impact. In viticulture, Agentic AI enhances vineyard management and precision wine production by analyzing aerial imagery and soil-climate metrics to guide pruning, irrigation, and harvest timing. These agents can even fine-tune the fermentation process and drive personalized marketing strategies, elevating both product quality and consumer engagement.
The same technology is transforming renewable energy surveying. In solar and wind farms, Agentic AI systems autonomously assess terrain, structural integrity, and environmental conditions using drones and sensors. They adapt operations in real time, support predictive maintenance, and boost long-term energy output and sustainability.
In aquaculture, Agentic AI solutions continuously monitor fish farms via underwater cameras and sensors. They maintain water quality by tracking pH, temperature, salinity, and dissolved oxygen, while also observing fish behavior to optimize feeding schedules—promoting healthier stock and more sustainable practices.
For open-pit mining, Agentic AI deploys drones, LiDAR, and satellite imagery to generate high-resolution 3D maps and monitor terrain changes. These systems perform autonomous inspections, coordinate fleet operations, and provide predictive insights to enhance safety and resource extraction.
By continually learning from real-time and historical data, Agentic AI agents empower organizations to operate more efficiently, make smarter decisions, and ensure long-term sustainability across critical sectors.
Inspecting Wynyard
Agentic AI can play a transformative role in surveying and inspecting crops in Wynyard by combining autonomous decision-making with real-time environmental awareness. Using drones equipped with multispectral cameras and soil sensors, these AI agents can monitor crop health, detect pest infestations, and assess soil conditions across large fields with minimal human intervention.
For example, an agentic system might fly over Wynyard’s canola or wheat fields, analyze chlorophyll levels to detect early signs of disease, and automatically recommend targeted treatments. It could also inspect irrigation systems, identify underperforming zones, and adjust water distribution accordingly—boosting yield while conserving resources.
In more advanced setups, these agents integrate with platforms like IBM Maximo to not only detect issues but also initiate maintenance tasks, order supplies, and notify field managers—creating a self-regulating agricultural ecosystem.
Surveying Farms & Crops
Agentic AI is revolutionizing how farms and crops are surveyed by combining autonomous decision-making with real-time environmental intelligence. These AI agents use drones, ground robots, and IoT sensors to monitor soil health, crop growth, pest activity, and weather conditions—without needing constant human oversight.
For example, an agentic system might detect early signs of drought stress in a specific field zone, then autonomously adjust irrigation schedules or alert farm managers. It can also identify weed infestations or nutrient deficiencies using multispectral imagery and recommend targeted interventions, reducing chemical use and boosting yield.
What sets agentic AI apart is its ability to act on insights—not just collect data. It can initiate maintenance tasks, reroute resources, or even coordinate with supply chains to align harvest timing with market demand. This leads to smarter, more sustainable farming that’s responsive to both environmental and economic pressures.
Inspecting Solar & Wind Farms
In solar farm development, agentic AI uses drones and computer vision to perform high-precision terrain mapping, assess shading and tilt angles, and evaluate structural integrity. These agents generate detailed site models and energy yield forecasts, helping developers optimize panel placement and system design. Once operational, they monitor panel performance, detect anomalies like dirt buildup or inverter inefficiencies, and trigger maintenance workflows—reducing downtime and extending equipment lifespan.
In wind farms, agentic AI analyzes meteorological data, wind shear, and turbulence to determine optimal turbine placement and hub height. During operation, it continuously monitors turbine performance using vibration sensors and machine learning models to predict mechanical failures before they occur. This predictive maintenance reduces costly repairs and ensures consistent energy output. Some systems even use wake-steering algorithms to adjust turbine orientation in real time, maximizing energy capture across the entire farm.
By integrating these capabilities, agentic AI enables renewable energy systems that are not only more efficient and resilient but also more adaptive to environmental and market conditions—accelerating the global transition to clean energy.
Surveying Open Pit Mines
Our Agentic AI is revolutionizing open-pit mining by enabling autonomous, adaptive systems that enhance safety, efficiency, and decision-making across the entire mine lifecycle. These AI agents operate with a degree of independence, coordinating tasks like surveying, monitoring, and maintenance without constant human oversight.
Surveying & Mapping
Agentic AI leverages drones, satellite imagery, and LiDAR to autonomously survey vast open-pit mines. These agents generate high-resolution 3D maps, track terrain changes, and assess slope stability in real time—reducing the need for manual inspections and improving safety for field crews.
Predictive Maintenance & Operations
AI agents monitor equipment health using sensor data and usage patterns to predict failures before they occur. For example, they can optimize haul truck routes, reduce idle time, and even adjust cornering speeds to extend tire life—saving millions annually in large fleets.
Resource Optimization
By analyzing geological, geomechanical, and mineralogical data, agentic AI helps identify optimal drilling zones and extraction strategies. These agents can also recommend blasting techniques and ore sorting methods to maximize yield and minimize waste.
Autonomous Coordination
In advanced deployments, agentic AI systems act as a network of cooperating agents—managing logistics, inventory, and scheduling in real time. This creates a self-regulating ecosystem where AI not only monitors but also initiates actions, such as rerouting equipment or triggering alerts.
These solutions are already being piloted in major mining operations, including iron ore and copper sites, and are proving essential in meeting rising mineral demand while lowering emissions and operational costs.
Inspecting Commercial Fish Farms & Fish Ponds
We also have Agentic AI solutions to survey fish farms by analyzing data from underwater sensors and cameras to track water quality parameters like temperature, pH, salinity, and dissolved oxygen. This helps maintain optimal living conditions and detect anomalies before they impact fish health. We also use using behavioral data and visual cues, agentic AI can determine the ideal feeding times and quantities—reducing waste, improving growth rates, and minimizing environmental impact.
Environmental & Water Quality Monitoring
Agentic AI systems use underwater sensors and computer vision to track key parameters like temperature, dissolved oxygen, pH, turbidity, and ammonia levels. These agents can autonomously detect deviations from optimal conditions and trigger aeration, filtration, or alert protocols—ensuring a stable and healthy habitat for fish populations.
Fish Health & Behavior Analysis
Through video analytics and pattern recognition, AI agents monitor fish behavior to detect early signs of stress, disease, or abnormal movement. Some systems can even identify individual fish and track their growth, enabling personalized health management and reducing the need for antibiotics.
Smart Feeding & Biomass Estimation
Agentic AI optimizes feeding schedules by analyzing fish activity and appetite in real time. This reduces feed waste, improves growth rates, and minimizes environmental impact. Simultaneously, AI models estimate biomass using sonar or image data, helping farmers plan harvests and manage inventory efficiently.
Infrastructure & Net Inspection
Advanced AI-powered drones and underwater robots can autonomously inspect fish pens for structural damage, such as holes in nets, which could lead to escapes or predator intrusion. These agents operate continuously, offering a level of vigilance that manual inspections can’t match.
Together, these capabilities create a self-regulating aquaculture ecosystem that boosts productivity, sustainability, and animal welfare.
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