Shelf Management in Retail
Every year, retailers lose billions in sales due to products being out of stock and improper shelving practices. Ensuring a good retail experience is crucial to winning customer loyalty and increasing customer value. AI and ML can be leveraged to automate the tedious manual gap check process by identifying all availability issues on shelves. Visual scanners aid in recognizing product locations, products that are out of stock and those that are past their best by date.
Insights from Property Listing Images
Reviewing large amounts of real estate listing images to extract attributes of the property is a tedious, manual task. Computer vision can analyze these images to automatically extract specific attributes like locality, decor, flooring type, types of rooms, and living space conditions. This assists real estate platforms to get a more automated evaluation of the property, cross-reference this data with existing information about the locality or area, and check for inconsistencies in the listing.
Medical Imaging & detection
Deep Learning has demonstrated remarkable progress in image-recognition functions. Medical imaging is one of the most performed tasks using this technology. AI methods excel at recognizing complex patterns in the images and providing assessments of medical characteristics. AI models can be an effective tool for analyzing medical ailments like cardiovascular abnormalities, lung diseases like pneumonia, the development of tumors and melanoma, and checking for fractures from high-resolution medical imagery. This helps to provide timely treatments to patients.
Fleet Safety (prevention)
Accidents are an almost unavoidable event when it comes to using automobiles. AI models are used to reduce chances of accidents occurring and ensure the safety of the driver and fleet. Using Object detection models on driving video telematics can track risky driving practices and irresponsible driver behavior.
Inspection is usually the first step in a damage insurance claims process, whether it’s an automobile, mobile phone or property. Assessing the damages to calculate an estimate of repair costs can be a challenging task for insurance providers. Deep Learning models can be used to detect the different types, area, and severity of damage with greater accuracy and automate the claims process.
Property Risk Assessment
Traditional approaches to property risk assessment might not be able to capture the entire picture. Inspections for risk assessment can be assisted by Artificial Intelligence. The imagery of property and its surroundings can be utilized to determine the risk of future claims. Computer Vision technology helps to detect characteristics like fire hazards, gas leak chances, natural calamity risks, absence of safety features, poor upkeep and existing damages. Insurers can provide coverage to their clients based on this assessment.
RISK & COMPLIANCE
Drone Based Inspection
Organisations rely on availability of utilities around the clock for their daily activities. Monitoring the security of these assets is a costly and dangerous task. Businesses incur large sums in deploying helicopters for inspecting power grids, oil & gas pipelines, wind turbines, solar panels and other assets . Using drones fitted with cutting edge Object Detection technology, these assets can be monitored in a very cost effective manner. Inspection officers can assess the risk associated with these assets, such as component integrity, wiring issues, aging infrastructure, material corrosion, vegetation overgrowth etc.
Weed Detection and Control
Volume spraying of herbicides for weed control fuels the formation of resistant varieties. Farmers also raise concerns about the increased exposure of their produce to these chemicals. Using Computer Vision to identify areas infested with weeds from crop imagery, AI can identify the precise regions where herbicides have to be sprayed. This reduces the chemical usage and concentrates it only to the required area, granting more nutrients for the crops and produces better yield, resulting in profitability.
Pest Detection and Control
Farmers lose billions yearly in agricultural losses due to pest infestations. Farm owners are now implementing Machine Learning for the detection and identification of these pests. Hi-resolution imagery of crops are taken as input for the AI model, which can accurately detect if there is a pest infestation, the infestation extent, the type of pest, and pest classification using Object Detection. Farmers can then use the right agrochemical pesticides to treat the infestation with reduced environmental impact.
LOGISTIC & SUPPLY CHAIN
Freight Container Inspection
To adhere to regulatory compliance, freight containers need to be monitored while out for shipment. Port Authorities inspect the containers for heavy exterior damages, proper sealing practices, hazardous or dangerous material stickers or tags, and container leakages. Manual inspections can be error-prone due to distance, container stacking, insufficient lighting, and poor positioning between the inspector and the container. A Computer Vision model, using ‘Object Detection’, can identify these attributes of the containers much more consistently. CCTV cameras placed around yards and container zones can capture container images. AI notifies Port Authorities if it detects any non-compliance in the container's attributes.
Personalized Advertising is quickly becoming the cornerstone of an effective marketing strategy. Marketers need to have contextual awareness while displaying ads to their target audiences across different platforms. AI assists marketers to place contextually relevant ads that are most likely to resonate with their target audience. A Computer Vision solution can analyze the content that is being interacted with by the user, such as images and videos, and deliver personalized ads based on the content, in real-time. In a similar manner, Marketers can also place different versions of the same ad campaign, catered to the individual’s taste. AI is able to make contextual understanding much more accessible to marketers, and deliver their ad campaigns around this.
Customers spend a lot of time in ineffective keyword searches for products that they wish to purchase, leading to reduced product discovery. E-commerce platforms implementing a visual search function, powered by Computer Vision, enables shoppers to take a photo or upload an image of an item of interest. AI analyzes the attributes of the item and can recommend similar products in their online and offline stores. This recommendation engine can be further enhanced using options to narrow down the search results by personal preference. AI ensures customers find exactly what they are looking for each time they visit the platform, greatly increasing sales revenue and opportunities to provide further product recommendations.
Objectionable Image Detection
In the real estate digital space, property listing images are aplenty. Oftentimes, buyers become frustrated at the lack of good quality images, and can quickly be turned off by examining inferior ones. Blurred, skewed, poorly-lit, digitally fabricated and duplicated images convey very little or misleading information about the property to the buyers. Real Estate platforms are leveraging AI in order to audit these images, detect images of poor quality, and retain the ones that provide a better viewing experience to the buyers.
Watermarks on property listing images are one way that competitors or third parties attempt to advertise on real estate platforms. Fraudulent agents may also upload images from disparate sources carrying their watermarks. It is a visual barrier, making listing photos less visually appealing and confusing buyers. AI, backed with computer vision, can be taught to comb through these images and detect watermarks much more efficiently and at a larger scale than a human reviewer. AI prevents real estate platforms from turning into a scam and spam-filled space and can prevent repeated offenders from creating new listings.
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