Automate and Control LTD

Category: Remote Sensing

  • Hyperspectral Machine Vision, what is it?

    Hyperspectral imaging (HSI) is a highly precise and non-intrusive method that captures high-resolution spectral images from objects. By capturing a series of images, each containing data from a narrow spectral band, the HSI sensor creates a hyperspectral cube, where each pixel in the image contains a complete spectrum. This technique allows for the identification of materials based on their distinct spectral signature. Above is the MV.X system we can integrate into your current production lines. for more information on it’s capability see MV.X

    HSI sensors operate by dividing incoming light into several narrow spectral bands, ranging from ultraviolet to near-infrared regions of the electromagnetic spectrum. The sensor measures the intensity of light at each wavelength, and the data is processed using various algorithms to produce a spectral signature of the object being imaged.

    In the food industry, HSI has several applications, such as quality control, food safety, and inspection. HSI detects foreign materials like stones, plastics, and glass in food products, defects in fruits and vegetables, such as decay, mold, and bruising. It can also detect the ripeness and freshness of fruits and vegetables and identify different varieties of fruits and vegetables.

    One study published in Food Control explored the use of HSI for detecting aflatoxins in peanuts, toxic and carcinogenic compounds produced by certain fungi that can contaminate crops like peanuts, cottonseed, and corn. HSI identified the spectral signature of the contamination, which enabled accurate detection and quantification of aflatoxin. This study proves the potential of HSI as a food contamination detection tool.

    Another study published in Food Analytical Methods investigated the detection of E. coli bacteria in ground beef through HSI. The researchers used HSI to identify the spectral signature of E. coli in ground beef and successfully detected its presence with high accuracy. This study showcases the potential of HSI for food safety in the meat industry.

    In conclusion, hyperspectral imaging sensors provide a non-intrusive and non-destructive way of identifying materials based on their spectral signature. In the food industry, HSI has many applications, and ongoing scientific research continues to explore its potential in areas such as food safety, quality control, and inspection.

    For more information on why implement hyperspectral imagery please follow this link. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=bc5a6e243b6ffcd79e1892974f02699194b01426

  • Precision Agriculture & Hyperspectral Remote Sensing Fused with LiDAR and GPS

    Perfect Fusion of Hyperspectral Imagery, LiDAR and Precision GPS

    Precision agriculture (PA) is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. LiDAR’s 3-D scanning allows you to see the shape and volume of your field and precisely measure its dimensions . The idea behind using LiDAR is to tie multi-year crop growth stability/characteristics to topological terrain attributes as well as monitor seasonal changes over time. The interest in the phytogeomorphological approach stems from the fact that the geomorphology component typically dictates the hydrology of the farm field.

    Hyperspectral Imagers, LiDAR and GPS are fused to collect data. Precision agriculture is enabled by the advent of GPS and GNSS. The farmer’s and/or researcher’s ability to locate their precise position in a field allows for the creation of maps of the spatial variability of as many variables as can be measured (e.g. crop yield, terrain features/topography, organic matter content, moisture levels, nitrogen levels, pH, EC, Mg, K, and others). Similar data is collected by sensor arrays mounted on drones. These arrays consist of real-time sensors that measure everything from chlorophyll levels to plant water status along with hyperspectral imagery. This data is used in conjunction with satellite imagery by variable rate technology including seeders, sprayers etc. to optimally distribute resources. However, this technology can be used directly in soil with wireless transmission of data without the need for human presence.

    Precision agriculture using drones can be used to capture images of a field to create orthophotos. These hyperspectral images contain multiple values per pixel in addition to the traditional red, green blue values (such as near-infrared and red-edge spectrum values) used to process and analyze vegetative indexes such as NDVI maps. The drones are capable of capturing imagery and providing additional geographical references (such as elevation) which allows the software to perform map algebra functions to build precise topography maps, which can be used to correlate crop health with topography. These topographic maps can be used to optimize crop inputs such as water, fertilizer or chemicals.

    Phenotyping Lab- Field – Greenhouse – Vertical Farming Systems

     

    Phenotyping UAV drone with LIDAR and Hyperspectral imaging
    Phenotyping landscape with trees and LIDAR