We use photogrammetry to capture 2D images ensuring accurate measurements, used for mapping, construction, environmental monitoring etc. At AeroIntel, our drones, equipped with high-resolution cameras, capture detailed imagery that we process into precise 2D models and maps.

In addition to photogrammetry, we utilize AI to automate tasks such as tracking wild game, monitoring site repairs, and inspecting areas for invasive species. This combination of drones, photogrammetry, and AI allows us to deliver fast, accurate, and detailed information, helping our clients optimize operations and make informed decisions.

Animal wellness and counting are crucial for both wildlife conservation and farm management. Advanced technologies like drones, AI-powered cameras, and thermal imaging play a significant role in monitoring animals in diverse environments. In wildlife, drones equipped with infrared sensors can count species accurately, even in dense forests or at night, while AI analyzes the footage to identify individual animals and detect changes in population trends. These methods help track endangered species, manage ecosystems, and control invasive species.

These technologies not only improve animal welfare but also enhance productivity and sustainability. Whether tracking migratory patterns or optimizing farm operations, modern tools revolutionize how we understand and care for animals.

Drones play a transformative role in assessing plant health indexes, offering precise and efficient monitoring over large agricultural areas. Equipped with multispectral and thermal cameras, drones capture high-resolution data across various light spectrums, including visible, near-infrared (NIR), and thermal wavelengths. These sensors measure critical vegetation indices like NDVI (Normalized Difference Vegetation Index), NDRE (Normalized Difference Red Edge), and SAVI (Soil-Adjusted Vegetation Index) to evaluate plant vigor, stress, and nutrient deficiencies.

Drones provide rapid, real-time insights by flying over fields and collecting detailed spatial data, identifying areas with water stress, pest infestations, or disease. Unlike manual methods, drones enable non-invasive, large-scale monitoring with minimal disruption to crops.

Farmers can use drone data to make data-driven decisions, such as optimizing irrigation, applying targeted fertilizers, and managing pest control efficiently. The integration of drones into precision agriculture not only enhances productivity but also promotes sustainable farming practices by reducing resource wastage and improving yields.

Area and volume calculations are essential tools for engineers and construction workers, especially when assessing construction sites. These calculations help estimate material quantities, optimize designs, and manage costs effectively. By using drones, LiDAR, and photogrammetry, construction teams can measure land area, building footprints, and excavation volumes with high accuracy.

For example, drones equipped with cameras and sensors can quickly survey a construction site, generating detailed 3D maps. These maps provide measurements of stockpile volumes, earthworks, or cut-and-fill requirements, reducing manual effort and human error. Engineers can also use this data to plan efficient layouts, ensuring compliance with regulations and safety standards.

Volume calculations are particularly useful for tracking material usage, such as concrete, gravel, or soil, ensuring accurate delivery and preventing shortages or wastage. By leveraging advanced technologies for area and volume assessments, construction teams can enhance productivity, reduce costs, and deliver projects on time with precision and reliability.

Object counting, such as trees, plants, and other items, is revolutionized by advanced technologies like AI, drones, and satellite imagery. In forestry, drones equipped with high-resolution cameras and AI algorithms can quickly count trees, assess forest density, and monitor growth rates over vast areas, aiding conservation and sustainable logging. Similarly, in agriculture, these systems help count plants, monitor crop health, and detect invasive species, allowing farmers to take targeted actions to optimize yields.

For environmental applications, object counting identifies invasive plants or tracks reforestation efforts by analyzing vegetation patterns and species distribution. AI-driven image processing and machine learning techniques enable accurate detection even in complex environments with overlapping objects or poor lighting.

This data empowers decision-making across various industries, helping conserve resources, protect biodiversity, and improve land management. Whether tracking individual objects or analyzing large-scale patterns, object counting tools bring efficiency and accuracy to ecological and agricultural monitoring.