machine vision application India

5 Compelling Machine Vision Applications for a Sustainable India

Sustainability has emerged as the need of the hour for countries across the globe. The Paris Agreement signed by 196 Parties, including India, aspires to limit global warming to below 1.5 degree celsius and attain net zero carbon emissions by 2050.  This calls for countries world-over to pivot their development strategies towards smart sustainability. Machine vision, a subfield of computer vision, can help various sectors including agriculture, energy, transportation, waste management, environment and more, in this transformative journey by delivering smart solutions to sustainability issues.

What is Machine Vision?

Machine vision technology equips machines with “sight”. The set-up includes lighting, cameras with sensors, processors, and communication systems. Lighting illuminates the environment or object of focus, the lens and sensor within the camera captures images of the object and converts them into a digital format, and the processor extracts meaningful insights from the digital data through its built-in software and machine vision algorithms. Based on the data gathered by the processor, the system communicates with other machines, robots or software through output channels.

Machine Vision System Applications in the Real World

Smart Farming

The agriculture sector in India is reeling under serious challenges including drastic climate change, shortage of labour and the persisting after effects of the pandemic. Machine vision technology is expected to revolutionise the industry by improving the quality of the produce and efficiency of processes, reducing wastage and manual labour, and helping farmers make profit-maximising decisions.

Typical applications include:  

  • Detection of abnormalities and diseases in fruits, vegetables and leaves by processing images through trained algorithms
  • Identification of water stress, pest stress and deficiency of nutrients in plants
  • Soil monitoring and mapping farmlands to crop areas through drones enabled with machine vision cameras and geothermal technology 
  • Automation of crop inspection, sorting and grading through hyperspectral imaging technology. The technology helps analyse the distribution of moisture and fat in the product and segment them based on size, colour, quality, defect and more. 
  • Counting fruits and vegetables with high precision and efficiency.
  • Identify areas that are prone to pests and administer pesticides in required amounts through drones equipped with spray guns and cameras  .
  • Computer vision-enabled phenotyping that helps farmers gather data into plant genetics to identify crops that are most sustainable and resilient.

Transportation Management

The transportation sector is undergoing a transformational change by switching to renewable energy and adopting ways to manage traffic with efficiency. The interesting applications of machine vision systems in transportation include: 

  • Realising autonomous cars through 3D time-of-flight (ToF) technology. The tech offers precise and accurate depth sensing capabilities for a wide range of use cases including driver monitoring, secure navigation, smart airbag systems and more. 
  • Sensors powered by High Dynamic Range (HDR) technology in autonomous cars help capture high quality information even in situations of high contrast such as tunnel entrances and exits. 
  • The automotive industry is also rapidly embracing the Electric Vehicle (EV) era by setting up new facilities or transforming their existing crude oil-based production lines to manufacture electric vehicles. Custom machine vision systems equipped with high-definition streaming cameras and high voltage battery inspection systems are interesting solutions to look forward to in this space.   
  • Intelligent Transportation Systems (ITS) with vision analytics that facilitate intelligent traffic management, emergency vehicle notification systems, electronic toll collection, V2X (Vehicle-to-everything) communication and more.

Waste Management and Garbage Segregation

Just like the other industries, the waste management sector has its own share of struggles as well. Manual and improper garbage segregation done by humans result in contamination. Lack of real-time monitoring of garbage bins results in delayed garbage collection and inefficient waste management. 

Machine vision facilitates the below in the waste management industry:

  • Digitization of end-to-end processes in waste management plants including collection, sorting and treatment of waste 
  • Intelligent algorithms can identify different components such as plastic, glass, metal and more from huge metric tonnes of waste while sorting and segregate them into specific waste streams
  • The automatic segregation and improved quality inspection powered by IR imaging and polarization machine vision cameras result in improving the quality of recycled material 
  • Automatic measurement of waste streams and real-time analysis on the end-to-end waste flow help the industry reduce risks, save costs and increase revenue.

Energy Management

The energy sector in India is actively seeking ways to leverage AI and ML to identify usage patterns, detect energy losses, optimise consumption, and forecast demand. The scope of machine vision technology in this space is limitless. 

  • Automated inspection of solar panels in the production line for defects, including scratches, micro-cracks, and broken or chipped cells through image preprocessing and pattern recognition. 
  • Monitoring large acres of solar farms for defects and alignment of solar panels’ through drones equipped with UV and IR imaging cameras 
  • Unmanned aerial vehicles (UAV) with machine vision cameras are also used to monitor windmills for rust, oil spills, coating damage and more. Scores are assigned to windmills based on the images captured which are later analysed by inspectors for maintenance.

Wildlife Conservation

With the rich biodiversity of India facing threats due to changing climatic conditions and illegal human activities, wildlife conservation measures have gained momentum over the years. Machine vision helps with efficient and increased data collection by expanding coverage and reducing costs, compared to conventional methods.

  • Helping in collecting large volumes of data from previously unreachable areas through high-resolution remote sensing cameras and sensors 
  • Facilitating the study of animal movements and behaviour through tracking tags, sensor arrays and machine vision cameras 
  • Preventing poaching activities through drones equipped with cameras and deep learning models that can locate and monitor endangered species
  • Monitoring wildlife in railway crossing and avoiding accidents through thermal and IR imaging cameras

The above mentioned opportunities presented by machine vision to build a sustainable India is just the tip of the iceberg. Being an evolving and dynamic technology, machine vision will continue to present new possibilities across industries to build a greener and circular economy for the future generations. 

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