Category: Industry 4.0

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How XR Technology is transforming the Maintenance and Repair Industry

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Applied Innovation Industry 4.0 Uncategorized

How XR Technology is transforming the Maintenance and Repair Industry

Everyone is raving about the new, intriguing technology known as XR. But what does XR actually imply, and when can this technology be used? Cross reality, also known as expanded reality, is a general word for several distinct but connected technologies, which include Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR).

XR, MR, VR, and AR

The terms XR, MR, VR, and AR are frequently used synonymously but there is a definite distinction between these. Virtual Reality is a type of XR that uses a head-mounted display (HMD) or smartphone, or other gadgets placed about an inch away from the viewer’s eyes to fully immerse the viewer in a simulated world. Here the display of the gadget completely fills the user’s field of view. However, not all XR is virtual reality (VR).

Similarly, Augmented Reality is a subset of XR that uses digital enhancements to improve the user’s perception of the actual world. Typically, a device’s camera is used for this, which records the real-world scene and superimposes digital components on top of it. For instance, augmented reality (AR) may phone’s camera to project game figures onto the screen of a smartphone, giving the impression that they are in the same room as you.

MR, or “mixed reality,” is a fusion of VR and AR. In other words, Virtual reality and augmented reality are combined to create Mixed Reality. Users can engage with both physical and digital objects thanks to MR’s anchoring of digital components to the real world. Usually, specialized gear, like Microsoft’s HoloLens, is used to accomplish this. Overall, it’s critical to comprehend the distinctions between XR technologies because each has particular advantages and disadvantages and is best suitable for particular uses.

Application of XR in Different Industries

XR technology by combining the physical and virtual worlds improves safety, efficiency, and productivity while reducing costs and downtime. It has the potential to revolutionize the way we work and is impacting many industries like Gaming and Entertainment, Employee Training, Customer Support, Healthcare, Property and Real Estate, and Retail.

Application of XR in Maintenance and repair


Maintenance and repair work is one of the most important applications where XR is having an impact. Technicians can obtain real-time information, such as directions, blueprints, and troubleshooting manuals, about the equipment they are working on by using AR overlays. This technology may increase the precision and effectiveness of maintenance and repair work, decrease delay, and eventually result in cost savings for companies.

Traditionally, techs have user manuals and blueprints to identify and fix equipment. This approach, though, can be laborious and error-prone. On the other hand, XR technology gives workers a visual depiction of the equipment, enabling them to swiftly recognize the issue and fix it. This is especially advantageous for sophisticated apparatus and equipment, where even a small error can result in expensive downtime and maintenance costs.

Additionally, step-by-step directions on how to fix or keep the equipment can be provided using AR overlays. This benefits technicians who may be inexperienced with a specific sort of machinery or lack the required knowledge. Technicians can more swiftly and correctly identify and fix machinery with the help of real-time guidance.

Repair workers as well can be trained using XR technology on how to operate and manage equipment. The use of VR models can give techs access to a regulated and secure virtual world where they can practice maintenance and repair tasks. This can lower the possibility of mishaps and equipment harm while training, as well as increase the techs’ effectiveness and accuracy in real-world situations.

Remote assistance can also be provided using AR graphics. With the aid of smart eyewear, techs can communicate in real-time with specialists who can assist them virtually throughout the maintenance or repair process. When working with complicated equipment that calls for specialized knowledge and experience, this can be especially helpful.

In general, XR technology has the power to completely transform the servicing and repair sector. Businesses can increase the precision and effectiveness of maintenance and repair tasks, decreasing delay and eventually saving money, by giving workers real-time information, step-by-step directions, and online assistance. It will be fascinating to observe how XR technology develops in the future and how it will help companies run more effectively and efficiently.

Please write to us at open-innovator@quotients.com to learn more about such innovative solutions and partnership opportunities.

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How AI is impacting the textile industry

How AI is impacting the textile industry [Image Courtesy: Pixabay ]
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Applied Innovation Industry 4.0

How AI is impacting the textile industry

The textile industry is looking for high-quality low-cost strategies to differentiate itself and take production ROI into consideration due to growing competition led by high labor expenses.

Problems with the manual approach

Most of the time, in the textile industry, inspecting yarn is done manually, which takes a lot of time and work. Operators stationed at various lines do the check, they have to pick up a variety of goods at random and examine them with their unaided eyes. They determine the fibers’ grade by visual inspection and separate them accordingly. Due to this manual approach wide variety of faults, including stains, deformation, knots, broken yarn, splitting, fuzzy edges, and incorrect color, missed inspections are also rather prevalent. Rule-based vision systems are prone to high rates of incorrect detections and require manual double-checking when errors are irregular or occur in large numbers. Yarn inspection requires a more dependable approach in order to increase labor productivity.

AI-powered solution

Using an AI-powered solution several kinds of yarn flaws may be detected and identified through picture analysis. The AI model can swiftly and precisely find faults to increase detection rates and manufacturing output while lightening the load on manual inspection. The technology can continue to refine the AI recognition process as the amount of accessible data grows and enable the speedy transfer of training results into multiple manufacturing lines.

This involves the use of an appearance tester that tests the samples of yarn taken from the lab. Vectors are defined and utilized as network inputs, and sample photos are taken and preprocessed. Then feed-forward neural networks are employed that had been trained using the back-propagation rule. Better outcomes may be achieved by using a multilayer neural network in conjunction with picture enhancement to estimate various yarn metrics. As a result, a modeling system may be effectively constructed.

Artificial intelligence (AI) can also be used in forecasting yarn properties and dye recipes. By analyzing past data on dye recipes and their outcomes and extrapolating this understanding to the characteristics of new dye recipes, AI may also be used to predict the quality of dye recipes. Machine learning algorithms or other types of AI techniques may be used to achieve this. To identify trends and forecast results, one method is to employ machine learning algorithms, which can be trained on vast datasets of yarns, textiles, and dye recipes. A machine learning model, for example, may be trained on a dataset of fibers with known attributes, such as strength and fineness, in order to predict the characteristics of new fibers. Similar to this, a machine learning model that has been trained on a dataset of well-known yarn attributes like tensile strength and elongation may be used to predict the properties of new yarns.

The advantages of implementing a machine vision system include an inspection accuracy of about 98 percent and each product may be inspected. Overall, the use of AI for yarn property prediction, fiber grading, and dye recipe prediction may assist manufacturers in improving the quality and effectiveness of their processes, resulting in significant cost savings and improvements in product performance.

Our innovators have developed solutions for computer vision for inspection and forecasting yarn properties and dye recipes. Some of these solutions have been successfully implemented at different levels. Please write to us at open-innovator@quotients.com to know more about these solutions.

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Drones for inspection of challenging internal environments

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Applied Innovation Industry 4.0

Drones for inspection of challenging internal environments

Visual inspections are required as part of most industries’ maintenance procedures. Using a drone to capture visual data on the state of an asset can assist inspectors in avoiding unsafe circumstances, lowering risk, and drastically lowering cost.

High-resolution Video Checks

Drones have several other advantages such as high-resolution video checks. This allows for more efficient and cost-effective examination of difficult-to-reach places such as pipelines and structures, eliminating the need for costly approaches such as rope access and scaffolding. Captured high-quality images may be used to conduct extensive condition evaluations.

Thermal Imaging

Thermal imaging may also be performed by drones. Inspections may be done in a highly effective and timely manner using aircraft-mounted thermographic imaging technology. Potentially dangerous hot spots that might lead to unanticipated downtime and maintenance can be identified promptly.

Photogrammetry

Another approach utilized by drones for inspection is photogrammetry, which produces the most precise data for 3D modeling and dimensional mapping for volumetric calculations. This significantly improves comprehension of an asset’s status to aid decision-making.

Fields of Application

Offshore projects are generally viewed as severe and demanding, and it is critical to limit errors and loss of production at both the installation and the inspection equipment to a minimum. For instance, a flare inspection on an oil-and-gas platform where the flare is still operational. The drones can here capture image- or thermographic data about the flare’s status while production continues unimpeded.

Drone inspection may also be used for onshore structures such as bridges on land, linking islands, or crossing divides in a landscape. Also for inspection of towering buildings such as wind turbines, where the drone obtains high-resolution photographs of potential flaws, allowing for detailed planning of repair work as the data obtained will assist avoid unpleasant surprises during the maintenance period.

Drone inspection is also useful in confined locations such as power plant boilers, fuel storage tanks, and so on. Visual inspections are desirable, but there are significant problems when deploying drones in limited locations. Drones, on the other hand, can provide good picture quality with real, natural colors by employing strong LED lighting.

Every day, workers all across the world evaluate dangerous interior places. Drones can thus undertake surveys of difficult inside settings more securely, economically, and effectively than human inspectors; thus, the time has come to transition to drones for internal inspection.

We have solutions for drone inspection that can be used in sectors like Renewable energy, the Oil and Gas Industry, Cement Industry, Mining Industry, and other traditional manufacturing industries.

For additional information on such solutions and emerging use cases in other areas, as well as cooperation and partnership opportunities, please contact us at open-innovator@quotients.com

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How Microfactories will transform Manufacturing?

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How Microfactories will transform Manufacturing?

A microfactory is a small-to-medium-sized, highly automated, technologically advanced manufacturing setup with a diverse set of process capabilities. It is often a production facility, the output of which may be scaled up by reproducing such setups in huge numbers. Because of the high-tech automated operations, microfactories use less energy, less material, and a smaller workforce. The microfactory idea also encourages the shrinking of manufacturing equipment and systems based on product dimensions. This helps to reduce the size of the plant, which requires less capital and decreases operational expenditures.

As micro-factories proliferate over the world, they will establish a uniform style of working and running, resulting in global production unity. On Similar lines to Cloud computing, Cloud manufacturing, a new production idea that converts traditional manufacturing resources into services and makes them available via the Internet by utilizing cloud computing, the Internet of Things (IoT), and virtualization is emerging. As companies like AWS offer standardized platforms on which a wide range of services and applications run, cloud manufacturing in the near future will have corporations supplying standardized micro-factories that handle the majority of contemporary industrial output.

Manufacturing as a Service (MaaS)

Cloud Manufacturing also referred to as MaaS or Distributed Production is one of the most significant opportunities made available by widespread company digitalization. It enables organizations to focus on product innovation while outsourcing the actual process, as well as crucial services and technology, to an outside party by using new technologies and linked services to improve production efficiency and business leanness.

Manufacturing as a service is the production of commodities using a networked manufacturing infrastructure. To put it another way, manufacturers utilize the internet to share production equipment in order to cut costs and produce better goods.

Just as cloud computing allows for instant access to pooled computer resources such as software, hardware, and data, similarly MaaS is driven by Cloud networked manufacturing. The cost of manufacturing infrastructure—machines, maintenance, software, networking, and other costs—is shared by all consumers. For starters, this results in cheaper production costs, more uptime for each machine, and increased manufacturing capacity for each organization.

These MaaS platforms are rapidly gaining traction in key industries such as automotive, aerospace, health care, and military. Major industrial enterprises have begun to use these platforms as well.

Our innovators have developed a new business model around MaaS that is expected to have a deep effect on the global manufacturing sector. We offer manufacturing services with complete visibility with significant lead time and capacity that is available for both startups and industries. CCTV camera-based machine vision capabilities assist in visualizing production processes digital twin and automate production data capture, monitoring, and analysis.

We would be delighted to hear from you and would like to discuss the opportunities for collaboration. Please write to us at open-innovator@quotients.com

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Robots for Inspection and Maintenance Application

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Robots for Inspection and Maintenance Application

Inspection and maintenance duties are essential in many industrial sectors, such as damaged infrastructure, tunnels, refineries, and old buildings. Companies spend billions of dollars every year on inspections and maintenance.

Mobile Robots


Mobile robots enable the automation of processes such as inspecting and maintaining situations that pose a risk to workers. There are hazardous or difficult-to-access situations for people, such as nuclear power plants, the chemical industry, where poisonous compounds are handled, or sites where there is a risk of collapse, among others. Mobile robotics can assure operator safety and penetrate difficult-to-reach areas. They can also assist to reduce the cost of operations and mistakes caused by weariness or bad environmental conditions. This has led to an increase in the demand for AMR (Autonomous Mobile Robots) both for end users and for R&D projects in recent years.

Robotic Crawlers

Robotic Crawlers provide a simple and rapid restricted space inspection option as part of a routine maintenance and monitoring operation. These robots use a distinctive track design to get access to locations that are just unattainable with existing technology. Crawlers are useful for routine or emergency inspections at petrochemical plants, nuclear power plants, hydroelectric facilities, refineries, and other facilities. This durable inspection robot’s adaptability provides an all-in-one solution for small and medium-sized pipes, tanks, boreholes, or other restricted locations where a downhole camera is required. Anyone who has to undertake remote visual inspections in restricted locations with limited access should consider adding these robots to their NDT toolset. There are several setup choices available to discover how this works.

Climbing Robots


Climbers are portable, remote-controlled machines that can ascend practically any vertical or inverted surface. Because they are handled securely from the ground, people are not exposed to perilous heights or toxic environments. Climbing robots must be built based on the intended duties and application sector. These factors determine whether locomotion principles or adhesion systems are appropriate, as well as the size of the robot. Such devices can scale walls, tanks, ships, building structures, dams, and towers, among other things. There are several configurations available according to their work and application.

Underwater Robots


Underwater robots help with inspections, repairs, and upkeep. These autonomous robotic vehicles eliminate the requirement for manually controlled surface boats. They feature a narrow, flexible shape that allows them to traverse great distances and do light inspection, maintenance, and repair tasks underwater in limited locations. The robots which are outfitted with a variety of important sensors and equipment may be put on both current and new fields. They can be used for visual examination, cleaning, and operating valves and chokes, among other things. This system allows for significant savings in subsea inspection and intervention expenditures, as well as time spent on inspections, repairs, and maintenance.

Inspection and maintenance robots can find applications in industries such as Petrochemical, Oil & Gas, Nuclear, Mining, and in Municipal and Underwater applications. We have solutions for all the mentioned applications and more, to access more information on these solutions please write to us at open-innovator@quotients.com


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Self-driving Robots for Industrial Automation

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Self-driving Robots for Industrial Automation

Autonomous vehicles (AVs) have long caught the attention of futurists and technology enthusiasts, as indicated by constant research and development in autonomous vehicle technologies over the last two decades.

Rapid advancements in robotics, artificial intelligence, computer vision, and edge computing capabilities are culminating in robots that may be able to think, see, hear, and move. AVs in the form of self-driving vehicles have generated both enthusiasm and fierce rivalry among automakers and technology firms.

Self-driving vehicle prototypes outfitted with lidars, radars, cameras, and ultrasonic sensors — as well as hefty computational powers beneath the hood to detect and avoid obstacles — are becoming prevalent in many places. We are now on the verge of fast deployment of advanced autonomous vehicle technologies in industrial applications, and the convergence of the Internet of Things (IoT) and AV technologies is set to re-make and re-imagine industries.

Rapid automation in e-commerce distribution centers and industrial facilities has resulted in a vibrant subset of robotic logistics centered on supply chains and automated material transportation. A combination of variables, including but not limited to a spike in e-commerce, mass customization of items, technological improvements, and shifting economics in supply chains, has resulted in a surge in demand for automation in materials handling.

We offer some products based on the use of technologies such as computer software and robotics to control machinery and processes to perform specific functions. Some of these are described below that can be used to achieve digital factory goals in a time-bound manner.

Autonomous Forklift: An autonomous forklift that is appropriate for material delivery applications in warehouses or manufacturing plants, as well as outdoors. It can move easily on asphalt, concrete, and cemented walkways.

It has a payload capacity of 2 Tonne/ 3 Tonne/ 5 Tonne for various circumstances and can lift goods up to a height of 3 Meter. It is a counterbalanced forklift that performs well on slopes and uneven floor surfaces.

Autonomous Pallet Transfer Robot: We also offer a self-driving industrial-grade pallet transfer robot capable of automatically carrying a payload of 1000 kg/2000 kg. It has dual 3D cameras located in the front and back. The back 3D camera aids with accurate pallet localization and a safe alignment technique for lifting pallets from the ground.

Autonomous Trolley Transporter Robot: With this, we also have an autonomous trolley transporter robot, an industrial-grade model designed for autonomous trolley transportation. It can move carts of various sizes and weights ranging from 100 kg to 2000 kg by attaching to them from beneath. It has 3D camera-based trolley localization and safely align technology, which allows it to accurately fasten the trolleys from beneath. The robot has a fully autonomous guiding system with dynamic obstacle avoidance.

To know more about these solutions and for product demo please write to us at open-innovator@quotients.com

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Robotic arms capable of perceiving, comprehending, and operating any item in any environment

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Robotic arms capable of perceiving, comprehending, and operating any item in any environment

For many established sectors, the previous several years have been transformative. The COVID inflection point has accelerated the trend of ICT adoption that had been steadily trickling into these traditional sectors.

Making Manufacturing Smarter

There have been a few tech adoptions in the industrial sector, but none have come close to the capabilities that deeptech (AI, IoT, and ML) has in making manufacturing smarter.

The most difficult problem in our market is to provide the best products and services at the lowest possible cost in the shortest amount of time. IoT and AI are opening up new options for the sector to improve service, reduce downtime, and raise efficiency while lowering production costs.

Manufacturers may access additional assets, acquire business insights from accurate data in real-time, and improve day-to-day operational efficiency and production performance using AI & IoT apps and sophisticated data analytics.

Robotic Innovations

Robotic innovations have had a favorable influence across fields, particularly in the industrial business. For years, industrial robots have played an important role in assisting manufacturing organizations in streamlining their workflow, closing skill gaps and addressing the labor issue, increasing production, and maintaining accuracy and consistency.

Visually Intelligent Robots

Enabling robots to conduct the Picking, Orienting, and Placing of goods directly from their containers has long been regarded as The Holy Grail of Robotics.

Visually Intelligent Robots can be the next big thing and may have a great impact on the manufacturing industry by simplifying automation. The robots now used in the manufacturing sector are unable to see and thus can not assist in Object Manipulation. AI/ML limited to just the color & depth of an object has been a challenging problem for this.

Visual Object Intelligence Platform

We have a solution for this: a visual object intelligence platform that allows industrial robotic arms to perceive, comprehend, and operate any item in unstructured surroundings.

We offer a system that adds the missing components of Visual Intelligence to Robotic Arms, allowing them to be Object aware and manage objects with more agility – adjusting to varied forms, orientations, and weights. 

This has the potential to reduce and standardize massive, bespoke production lines into LEGO blocks of micro-factories. Some of the tasks it can perform like Picking and Placing Untrained Objects from Any Untrained Picking and Placing a Variety of Objects Orientation.

Our robots can work on a wide range of items without any prior training thanks to the patented vision and intelligence layers. This serves as the foundation for universal object manipulation and, by extension, labor automation.

The platform is driven by modern technology and can distinguish between sight and vision. It enables robots with human-like eyesight and adaptability to grab even Mirror-Finished items without any pre-training (a feat that existing ML systems are incapable of accomplishing). It employs technologies such as Auto-Focus Liquid Lens Optics, Optical Convergence, Temporal Imaging, Hierarchical Depth Mapping, and Force-Correlated Visual Mapping for achieving this result.

These intelligent robots can grasp the aspects of an item and re-orient them based on their needs. The AI and Machine Learning algorithms assist robotic arms in processing tasks even in unstructured environments and aligning them in the best way feasible. These are also cost-effective and robust, and dependable.

The platform can find application in the manufacturing sector and may also assist warehouses, logistics, and industrial kitchens streamline duties. To know more about this solution and for product demo please write to us at open-innovator@quotients.com

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Applied Innovation Industry 4.0

Visual Inspection System improving Production Process

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Applied Innovation Industry 4.0

Visual Inspection System improving Production Process

Manufacturing operations attempt to provide the greatest level of quality at all stages of the manufacturing or assembly process. This requires quality checks that need visual confirmation to verify that the pieces are in the correct places, have the correct form, color, or texture, and are free of flaws such as scratches, pinholes, foreign particles, and so on. Because of the volume of inspections and product variation, as well as the fact that flaws can appear anywhere on the product and be of any size, automating these visual quality checks is extremely challenging.

A visual inspection enables the production process to be improved. The vision inspection system has sensors and cameras and relies upon computer vision technology. A visual inspection machine compares two objects in order to provide a response or result. For performing the comparison, vision inspection systems contain all of the information required to categorize all of the items included in the inspection.

To decide which elements will pass the comparison and which will fail, the visual inspection machine incorporates photographs of past tests that were deemed successful. The cases of ideal elements, the elements to be classed, and those that will pass the tests are included in the system, both visually and by information from another class. Those elements that are included through images serve as a guide to be able to compare all the others, as stated earlier this is the visual comparison.

Visual comparison occurs when one piece is placed next to another, observed from multiple perspectives, and able to produce some form of link between them. The qualities to be compared are observed from various perspectives, first to make them correspond in their orientation and allow for a more accurate comparison, or it may also be accomplished by re-creating the photos in 3D format, superimposing one over the other, and describing the differences.

We have solutions for object recognition, fault detection, and process control. Our visual defect and dimensional sorting solutions for a variety of items deliver high productivity with excellent product handling and better inspection efficiency. These solutions are designed with the customer’s needs in mind and are highly customizable to the user. It is combined with cutting-edge in-house software that is dependable and accurate, resulting in the best final product.

Some key features of the solution are:

– Real-Time Monitoring
– Resident Database SQL
– Remote Control and Setting
– Vision Software Programmable by User
– Statistical Reports easily accessible through UI
– Machine Vision Software
– Accuracy up to ±10 microns
– Support for multiple Camera units
– Run as a Turn-Key system
– Simple Setup and Adjustments
– Short Setup Time for multiple codes

To learn more about this product and how you can use it to grow your business, increase productivity, improve quality, and create a better working environment for your employees, please contact us at open-innovator@quotients.com.

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Cobots making automation simpler for businesses worldwide

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Applied Innovation Industry 4.0

Cobots making automation simpler for businesses worldwide

With Industry 4.0, robots’ role in intelligent production is expanding. The major objective is to increase production profitability, which is partly dependent on the organization of safety and efficient human-robot interaction in a shared work environment.

Robotic technologies incorporated with intelligent manufacturing can help to increase production automation while maintaining safety compliance. Robots’ mobility and compactness enable them to enhance the manufacturing process and increase efficiency.

The capacity to move robots outside of boundaries and set them near humans was a significant breakthrough in robotics. Every year, the market for robotic solutions expands. This suggests that there is a considerable demand for the use of robots in intelligent manufacturing. We can already observe how the major players in automated manufacturing have taken the first steps toward Industry 4.0.


A collaborative robot (cobot) is a robot designed to operate alongside humans. These are robots that are low-cost, safe, easy to install, and can make automation simpler than ever, even for small and medium-sized businesses worldwide. Cobots are meant to operate alongside people, making automation easier than ever for organizations of all sizes. All of these advantages have made cobots game changers in a wide range of applications. Additionally, these are excellent productivity tools for practically any manufacturing since they assist everyone in the organization in meeting performance goals.


We have solutions that make robots accessible to everyone. Human-robot interface technology that can be operated by experts or novices, without the need for them to be fluent in any programming languages or proprietary APIs. To do this, it is designed and manufactured from the ground up to seamlessly combine hardware and software with built-in collaboration capabilities, plug-and-play application adaptability, and, most crucially, the ability to operate securely alongside people without the use of any safety barriers.

These robots are totally software-driven, with a sophisticated software platform available via an intuitive and responsive interface that can be used to teach, collaborate, automate, and connect with a manufacturing ecosystem.

To know more about this product and learn how you may expand your business, boost productivity, enhance quality, and create a better working environment for your staff with these solutions please write to us at open-innovator@quotients.com.

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Intelligent Video Analytics Transforming Manufacturing, Hospitality, Transportation, Healthcare, Retail, etc

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Intelligent Video Analytics Transforming Manufacturing, Hospitality, Transportation, Healthcare, Retail, etc

Video analytics, also referred to as video content analysis or intelligent video analytics, in recent times has been at the center of attention in both the industry and the academic world.

Advances in Deep Learning aiding Video Analytics

With advances in Deep Learning research and expanded availability of video data, video analytics now allows for the automation of tasks that were once possible by a human intervention only. This allows it to be used in a number of applications ranging from monitoring traffic jams and alerting in real-time, to analyzing customers’ flow in retail to maximize sales.

In Deep Learning, a subset of AI, a machine is exposed to volumes of tagged data allowing it to learn and recognize and identify the same information in new data sets imitating the way a human works. Deep Learning offers advantages like faster analytic output, improved processing performance, and increased object detection, accuracy, and classification.

Intelligent video analytics automatically recognizes temporal and spatial events in videos and performs real-time monitoring but it can also be used to analyze historical data to find insights. It can recognize objects, object attributes, movement patterns, or behavior related to the monitored environment are detected.

Some applications

Video analytics has the potential to be widely used in industries such as manufacturing, hospitality, education, retail, and others. We are discussing a few of them.

Healthcare

Integrating video analytics into legacy CCTV systems can transform cameras into much more proactive intelligence tools that can be used to ensure the safety of patients, staff, and visitors. Some of the most common problems like theft, infant abduction, and drug diversion can be detected and checked.

Mental healthcare is another area in which video analytics can be used to analyze facial expressions, and body posture to alert the hospital staff. It can also play a role in the at-home monitoring of older adults or people with health issues

Further, the data collected can be used to generate insights that can help to shorten wait times and achieve business goals by managing the staff according to patterns in the footfall of patients.

Transportation

Video analytics can be used in reducing accidents and traffic jams by dynamically adjusting traffic light control systems by monitoring traffic. By recognizing situations that may turn fatal in real-time, it can raise alerts, and even in the case of an accident, these systems can trigger an alarm to security and healthcare institutions to take action apart from that it can also serve as evidence in case of litigation.

Video analytics can also perform tasks like vehicle counting, speed cameras can detect traffic movements and license plate recognition can spots stolen vehicles or vehicles being used in a crime. It can also generate high-value statistics to assist in making infrastructure-related and other policy decisions.

Retail

The retail industry can use video analytics to generate insights and actionable information on customers’ behavior and buying patterns through their key characteristics like gender, age, duration and time of visit, walkways, etc. These algorithms can also be used to recognize previous customers and improve customer experience and provide personalized service. Video analytics can also play a role in developing anti-theft mechanisms by identifying shoplifters.

Manufacturing

Video analytics can improve productivity, reduce downtime and ensure staff health at the manufacturing facility by enhancing operations and management efficiency.

Smart cameras can be used to predict potential interruptions, evaluate specific bottlenecks and reduce downtime by generating alerts to take proactive action immediately. It can also optimize the number of employees in the production facility and improve overall productivity. Inventory management can also be enhanced by analytics as the warehouses can be monitored for their capacity. The use of machine vision can help in inspection and improve quality control.

Video analytics can also warn of situations that may pose threats to people, products, or machines by detecting movements and identifying conditions. Video analytics can provide round-the-clock security and alert commercial as well as residential buildings and prevent potential break-ins.

Video Analytics Approach

Video content analysis can be done in real-time or post-processing. Also, it can be centrally on servers that are generally located in the monitoring station or can be embedded in the cameras themselves, some times a hybrid approach is adopted.

There are startups that are working on Video Analytics and have successfully deployed their solutions across various sectors such as hospitality, retail, manufacturing, pharma, and food. To more about evolving use-cases and startups in different domains please write to us at Open-innovator@Quotients.com

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