The applications of image analytics are both compelling and pragmatic for enterprises today. There is no vertical that is not tapping, or not thinking of, image analytics to solve problems and create opportunities. The excitement is evident – when you consider these examples.

Among many other breakthroughs that have redefined how businesses cut costs and inefficiencies, while also generating new revenue pockets – image analytics comes on top of the radar. Its adoption-curve reflects the pronounced effect it has left on many enterprises across the globe. And we may have barely scratched the surface here.

What is Image Analytics?

Images were around us in the last decade also, and the decade before that. But a lot of advancements have happened that have completely upended the way we used to think of images. An image used to be just some random visual data – like a customer’s face in the store CCTV storage, or the topography document of a mine, or a picture of a shelf in a warehouse or a pipe’s image in a refinery or a bank document or the photo of a damaged car taken by an insurance agent.

Not anymore. These images are more than what they used to be. They are adding deep value and tipping points to the business strategies of retailers, mining giants, banks, insurance companies and many more enterprises. They are unlocking efficiencies that were never even considered before. They are unraveling fresh opportunities to mint revenue and create customer delight as well.

What has changed? Basically, images have been empowered with speed, real-time data and action, depth, storage scale, automation and intelligence now. An adjacent space of technologies has emerged and been strengthened – thus, making image analytics a viable proposition for businesses.

Some noteworthy ones that we can briefly take a glance at are:

  1. Smart cameras, image processors, optical recognition, and grayscale machine-vision algorithms
  2. Sophisticated optical sorting, better stereography and morphological image processing
  3. Robotics, drones, Augmented Reality (AR), and Virtual Reality (VR)
  4. Algorithms and models that can manage the complexity of many objects and shapes – like deep learning models, Convolutional Neural Networks (CNNs) and Machine Vision
  5. Image capture, processing, remote sensing, real-time processing, and advanced storage

Use cases of Image Analytics

Any business that has got images as data – in any form, from any source and for any duration – is a good candidate for wielding the advantages that this genre of analytics can proffer. Images can tell everything and anything – from insights about customers, to alerts about a faulty machine, to the authenticity of a document, and to the patterns that can shape to be of a big value for a business decision.

Let us consider some examples.

Use cases of Image Analytics in Marketing and Retail:

Images are adding constant and fresh data for marketers – in many areas. Like a social media post, a customer face, a complaint, a shelf’s condition, and a shopping cart. They can be converted into many ways of marketing value.

  1. For better and deeper customer understanding
  2. For creating precise, but non-intrusive customer intimacy
  3. For creating new sources of customer value and revenues
  4. For improving in-store execution
  5. For real-time merchandizing recommendations
  6. For enhancing long-term customer value
  7. For pre-empting customer complaints and issues by finding gaps in product quality and service in advance
  8. For tracking customer moods and preferences
  9. For weaving in AR and interactive experiences with product purchase journeys
  10. For creating face-recognition-based e-commerce payment systems

Use cases of Image Analytics in Oil, Mining Fields and Refineries:

The risk and scale of a sprawling refinery or oil rig are high and unpredictable. That’s why these enterprises have to make sure that they balance safety and exploration in the most optimum way possible. Images can help them strike this tough balance. These images can be taken through drones or can be automated with nano-bots inside pipes and equipment. Robotics, LiDAR (Light Detection and Ranging)-based mapping and UAVs (Unmanned Aerial Vehicles) can also add to this visual data in a way that is safe for humans but also of immense value to ‘humans in the loop’.

  1. Avoiding accidents through real-time alerts and predictive maintenance
  2. High-resolution mapping and surveys can help to find areas with maximum exploration value
  3. Risk mitigation and better compliance in danger-prone areas
  4. Use of motion and pneumatic system parameters, pressure, airflow, pressure, actuation speeds, and motor vibration – along with image analytics to increase machine uptime

Use cases of Image Analytics in Real estate and Infrastructure:

For a business that is in the road or transport or construction domain, the tricky part never changes. Costs run on a long-lifecycle graph of the project and the returns start arriving way after a project is executed. That’s why these businesses need a tight grip on unnecessary costs, wastage of resources (equipment and human), productivity losses, and scope/time creeps. Image Analytics becomes a savior for these very scenarios.

  1. Better control on project timelines by super-imposing a property’s image with an immersive augmented-reality environment
  2. Use of high-definition surveys and geo-location services for project collaboration
  3. 5D building information modeling and visualization
  4. Real-time dashboards for engineers and project managers
  5. Red flags for accidents and idle spots

Use cases of Image Analytics in Manufacturing:

Factories have found a new sense of relief and efficiency by using image analytics in many areas. The scalability and integration-ease of image analytics tools comes to the fore as a special attribute here. Plants and production cycles can be optimized with the visibility and control that comes easily with Image Analytics.

  1. In Auto Replenishment and product reordering
  2. In inventory management and supply-chain optimization through GPS-based vehicle tracking and truck fulfillment
  3. Predictive machine maintenance by real-time fault and leakage monitoring
  4. Enhanced level of safety, smart sensor-based fire systems, intelligent surveillance like Automated Optical Inspection (AOI)
  5. Robotics-enabled cleaning and sensor-based waste management
  6. Strong plant management and machinery control via easier asset-tracking applications and IoT-image embedded solutions
  7. Augmented production capabilities through intelligence and analytics
  8. Deeper and rigorous quality control through real-time inspections

Use cases of Image Analytics in Agriculture:

The right sensors and maps have emerged in the far-off fields of farmers also. That makes these farmers smart and confident because they can watch their crops, the weather, the pests and irrigation quality without wading their feet in inhospitable conditions. Image analytics empowers them with actionable intelligence about remote events.

  1. Use of images in pest detection
  2. Better, and faster, identification of nutrient deficiencies
  3. Improved yield management
  4. Adaptability to weather changes
  5. Crop-monitoring through object-tracking
  6. Accomplishing maximum land usage
  7. Higher crop quality, and value, due to real-time grading, inspection, vegetation measurement, irrigation, sorting etc.

Use cases of Image Analytics in BFSI:

A lot of areas exist in this vertical where the propensity for fraud or errors is huge. These are also areas where a lot of room is still present for cutting costs and expanding revenue. This makes the use of image analytics well-timed and well-applied here:

  1. Quick, accurate and transparent claim processing through real-time images of damages
  2. Fast and compliance-friendly KYC processes
  3. Remarkable speed improvements in customer-service
  4. ATM safety and security
  5. Control of fraudulent behavior
  6. Prompt complaint resolution
  7. Easy and cost-effective documentation

That’s not all. An airport can provide self-check-ins, a law enforcement authority can run faster investigations, a smart city can deliver smooth services through intelligent and real-time surveillance, and a hospital can accelerate diagnosis and treatment – all through the deployment of the right image analytics solution.


Getting started with Image Analytics

Image recognition alone has grown as high as $23.82 billion market in 2019 and is slated to reach $86.32 billion by 2027. Other estimates say that the global image recognition market would touch $109.4 billion by 2027. The report from Grand View Research also points out how figure identification, like facial or object recognition, visual geo-location, barcode reading, and automated driver assistance have been strong indicators here of just how versatile this technology is. According to Allied Market Research, the global image analysis software market would register substantial growth in the near future and this would be due to drivers like rise in adoption of image analysis software for healthcare & life science industry, rise in cloud deployment model for low cost of installation, etc.

All these buoyant estimates of growth, however, also point out how complexity, integration hassles, hardware issues, management burden, lack of skills and understanding continue to stay as challenges for businesses interested in image recognition and analytics. To add to that the fundamentals of data cleaning, preparation, extraction, governance, and integration also stay as tough spots for many enterprises. As the Deloitte’s survey ‘State of AI in the Enterprise’ unraveled, at least 40% of adopter organizations exhibit low/medium level of sophistication across a range of data practices; while a third of executives shared that data-related challenges are among the top three reasons that hamper their company’s AI initiatives.

That’s exactly why you need a good partner with the best expertise and resources to deliver the value you are looking for, without the headaches.

As exciting and much-awaited as these applications of image analytics look, let us remind ourselves that so much more is possible by discovering more innovative uses where this technology can be explored. We have, indeed, barely scratched the surface.

Start and go deeper. Talk to us and join the smart breed!