Get ready for the future of manufacturing! The fourth industrial revolution (4IR) is taking the industry by storm, ushering in a new era of technological advancements. From computer vision to artificial intelligence, robotics, and the industrial internet of things (IIoT), 4IR technologies are revolutionizing the way factories operate. This transformation presents a multi-trillion dollar opportunity, paving the way for factories to achieve greater accuracy, efficiency, and safety. Thanks to the power of computer vision, machines can now automate strenuous tasks, detect product and machinery issues, and improve safety conditions for workers by leveraging visual data and converting it to actionable insights. With these cutting-edge technologies at our fingertips, the future of manufacturing is looking brighter than ever!

As competition in the industry heats up, companies are looking for innovative ways to stay ahead of the game. Manual quality inspection processes in manufacturing units are often time-consuming and prone to errors, leading to significant revenue leakage from faulty products and wasted resources. One technology that’s really stealing the show by offering automation? Computer Vision. This amazing AI technology allows computers to see and understand visual data, making it a game-changer for the manufacturing world. By using computer vision to optimize manufacturing processes, businesses can reduce revenue loss, boost productivity, and increase their bottom line.

Computer vision technology is a vital component of Industry 4.0, transforming the way manufacturing plants operate. AI algorithms can be applied to existing CCTV systems or additional drone cameras to reduce revenue loss in manufacturing units by automating quality control and inspection processes. This technology can help identify defects or anomalies in real-time, reducing the need for manual inspections and increasing efficiency and productivity.

Real-world examples and statistics demonstrate the potential value of this technology with estimated ROIs ranging from 10% to 60%. As the manufacturing industry becomes increasingly competitive, computer vision will become a secret weapon to dodge the revenue loss, gain a competitive advantage and take your manufacturing enterprise to the next level.

Assembly Line Optimization

Computer vision can optimize assembly lines by reducing the time and effort required to complete tasks. This technology can detect and track objects, recognize patterns, and analyze data in real-time. This allows manufacturers to identify bottlenecks, improve process flow, and reduce waste. One example of assembly line optimization using computer vision is Ford’s use of the technology to improve their paint job process. Tom Dougan, project manager, global paint applications at Ford said, “We are trying to find things that are almost beyond the threshold of human detection. The operators used to spend 70% of their time searching the vehicle over, maybe finding something, maybe not.”

He continued, “Now, (with computer vision technology), they are able to focus 90% of their time on polishing the vehicle and making sure that it meets our standards for quality.” By using cameras and sensors, they are able to identify and eliminate defects in real-time, reducing their paint rejection rate by 80%.

Defect Detection

Another application of computer vision that can identify defects in products, such as scratches, cracks, or missing components. By detecting defects early in the manufacturing process, companies can reduce waste, improve product quality, and avoid costly recalls. By using AI-powered visual inspection, Nestle is able to identify and remove defective and broken products, detect even transparent objects in any position and detect laws, missing spoons etc before they reach the market, reducing their waste by 30%.

Nestle also is using computer vision to boost manufacturing efficiency in some of their KitKat manufacturing lines that are self-regulating. “We have loops in those lines, so they detect the product quality, they measure the attributes of the wafer, for instance, and then they regulate the process back,” said Stefan Palzer, Chief Technology Officer. “So, it’s a self-controlling mechanism. But we are also employing machine learning approach for preventive maintenance. So, that allows us to reduce downtime of our lines”, he added.

Predictive Maintenance

Computer vision can also be used for predictive maintenance, which allows manufacturers to identify and fix potential problems before they cause downtime or breakdowns. This technology can monitor machines and equipment, analyze data, and predict when maintenance will be required. This can save companies time and money by reducing unplanned downtime and avoiding costly repairs. One example of predictive maintenance using computer vision is Siemens’ use of the technology to monitor their gas turbines. By using AI-powered visual inspections, they were able to detect and repair potential issues before they caused downtime, correcting costly mistakes before they occurred, resulting in a 10% increase in turbine availability.

Volkmar Sterzing, Head of RG Learning Systems, Seimens AG states, “We were surprised at how much better the gas turbines could be run this way. To ensure that a gas turbine runs optimally, you always have to search for a balance in which several undesired effects such as combustion dynamics, loss of efficiency and emissions are kept as low as possible. If you improve one variable, you will worsen a different one. Artificial intelligence knows how to find the sweet spot.”

Quality Control

Finally, computer vision can be used for quality control, which allows manufacturers to ensure that their products meet the highest standards. This technology can analyze visual data, identify defects, and sort products based on their quality. This can help companies reduce waste, improve product quality, and increase customer satisfaction. Coca-Cola’s use of computer vision to ensure quality control using an automated visual AI based system is a real-world example of Computer vision visual inspection that detects liquid level, bottle cap missing, deformed bottles, missing label, and more, reducing their defect rate by 30%.

Estimated ROI of Computer Vision Technology in Manufacturing Sector

The potential return on investment (ROI) of computer vision in manufacturing is a captivating realm with varying outcomes. Delving into the depths of assembly line optimization, we witness ROI spanning from 10% to an astounding 30%. In the realm of defect detection, the ROI ascends to remarkable heights, reaching from 20% to an impressive 50%. As we unravel the prospects of predictive maintenance, ROI manifests within the captivating range of 15% to a staggering 40%. Finally, venturing into the realm of quality control, ROI soars to remarkable levels, encompassing an extraordinary spectrum of 25% to a mind-boggling 60%. These estimations, grounded in real-world examples and compelling statistics, underscore the immense value that computer vision can bring to the manufacturing industry.

Wrapping up

Computer vision is a powerful technology that can help dodge revenue loss for manufacturing plants. By optimizing assembly lines, detecting defects, predicting maintenance, and ensuring quality control, companies can reduce waste, improve efficiency, and increase profitability. Real-world examples and statistics demonstrate the potential value of this technology, with high ROI. As the manufacturing industry becomes increasingly competitive, computer vision will become an essential tool for companies seeking to gain a competitive advantage.

As supply chain managers, you understand the significance of inventory management in ensuring operational efficiency and customer satisfaction. With the help of AI-powered visual recognition technology, real-time stock management can be achieved, providing unparalleled accuracy and transparency in supply chain operations. In this post, we explore the benefits of real-time inventory visibility and how it can optimize supply chain management.

Benefits of Real-Time Inventory Visibility for Supply Chain Management

Inventory management automation is a critical challenge in supply chain management. Accurate and timely current stock status tracking and control are crucial for organizations to meet customer demand while minimizing excess inventory and associated costs. Inaccurate inventory records and inefficient inventory management can result in stockouts, delayed order fulfillment, reduced customer satisfaction, and decreased revenue. Additionally, inventory management becomes even more complex in global supply chains, where multiple locations, languages, and regulations must be considered. Therefore, efficient and effective inventory management is essential for successful supply chain operations and requires advanced technology and sophisticated processes.

Here are the benefits of real-time inventory visibility:

Smart Resource Allocation
Stock management automation lets supply chain managers allocate resources effectively and automate the process. With accurate and timely insights, managers can prioritize high-demand items and ensure that resources are allocated to where they are needed the most.

Accurate Forecasting
Dynamic inventory monitoring enables accurate forecasting. By tracking inbound and outbound stock and conducting regular stock audits, managers can better predict demand and expand distribution. This leads to better decision-making and helps avoid excess inventory and stock shortages.

Optimal Inventory Levels

Stock optimization is critical for supply chain management. With real-time inventory visibility, managers can ensure optimal stock levels by avoiding overstocking and stock shortages. This improves efficiency and reduces the risk of inventory obsolescence.

Also Read: Common Warehousing Mistakes and How You Can Avoid Them

Inventory Visibility
Real-time inventory visibility provides complete visibility of stock levels, location, and movement. This helps managers to track inventory in real-time and identify any issues before they become problems. This helps improve customer satisfaction by providing accurate information on order fulfillment status.

Increased ROI
With optimized inventory levels, supply chain managers can reduce inventory holding costs and increase cash flow. This allows companies to invest in other areas of the business.

Increased Demand Fulfillment
Efficient inventory management automation ensures that popular items are always in stock to meet customer demand. Accurate information about fulfillment schedules improves the customer experience and helps to build brand loyalty.

Supply Chain Transparency

Immediate stock availability tracking improves supply chain transparency by providing accurate information about stock levels and movement. This helps to identify bottlenecks and inefficiencies, leading to improvements in supply chain processes.

Operational Efficiency
Continuous inventory status monitoring streamlines supply chain processes and improves operational efficiency. By reducing manual processes and providing real-time information, managers can optimize inventory management and focus on value-added activities.

Real-time inventory visibility is essential for supply chain management. By providing accurate and timely information, managers can optimize stock levels, improve customer satisfaction, and increase ROI. With the help of AI-powered visual recognition technology, real-time stock view can be achieved, providing unparalleled accuracy and transparency in supply chain operations.

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Top 10 Computer Vision Use Cases for Manufacturing Sector

The aviation industry is a critical sector that relies on accuracy, precision, and safety. Computer vision technology is becoming increasingly popular in the aviation industry to improve operational efficiency and enhance safety measures. In this article, we will explore the role of computer vision in the aviation industry, including statistics related to its usage and benefits.

The aviation industry is a complex and demanding sector. It requires high levels of accuracy and safety. Computer vision technology is gaining traction in the industry. With an increasing number of airlines and airports adopting the technology to streamline operations and improve safety measures. In recent years, the use of computer vision technology in the aviation industry has increased, and the statistics support the benefits of this technology.

Challenges Faced by the Aviation Industry

The aviation industry is a complex and rapidly evolving industry that faces a wide range of challenges. Some of the most significant challenges include:

1. Safety: Safety is the most critical challenge faced by the aviation industry. Accidents and incidents can lead to loss of life and damage to property. The aviation industry has made great strides in improving safety through technology, training, and regulation manually. However, the risk of accidents are not completely eliminated.2. Security: With the increased threat of terrorism and other security concerns, the aviation industry must continuously adapt and improve its security measures to protect passengers, crew, and aircraft.

3. Cost Control: The aviation industry is highly competitive, and airlines must continuously work to reduce costs while maintaining high levels of service. Aircraft maintenance and components cost, labor costs, and airport fees can all have a significant impact on the profitability of airlines.

4. Regulations: The aviation industry is subject to a complex web of international, national, and local regulations. Compliance with these regulations done manually can be costly and time-consuming for airlines and other industry stakeholders.

Computer Vision Use Cases in Aviation industry

Computer vision technology has a variety of use cases in the aviation industry, including:

Predictive Maintenance

According to a report by MarketsandMarkets, the global market size for computer vision in the aviation industry is expected to grow from USD 1.5 billion in 2020 to USD 3.6 billion by 2025, at a CAGR of 19.7%. This growth is driven by the increasing demand for automation and safety measures in the aviation industry. Enable the detection of potential issues before they cause significant problems. Expect real-time monitoring and analysis of aircraft components, improving safety, and reducing maintenance costs. General repairs and maintenance can be done with the combination of computer vision and IoT systems. Deploy detection and analysis of potential maintenance issues to perform repairs more efficiently. It is now possible to inspect aircraft components, predict when maintenance is required, enabling timely repairs, preventing breakdowns, and reducing repair costs in the aviation industry. This not only brings a significant cost reduction, but also boosts aviation safety by multi-folds.

Security and Surveillance

The aviation sector uses computer vision and IoT technologies to enhance security and surveillance measures, detect and prevent security breaches, theft, or vandalism. This includes features like facial recognition, object detection, and monitoring of passenger behavior through cameras and sensors. These systems can detect potential threats, improve passenger flow and safety, and enable more efficient operations.

Object Detection and Recognition

Object detection and recognition using computer vision can enhance safety and security. This technology can identify and track objects in real-time, allowing for early detection of potential hazards and faster response times. It is commonly used for baggage screening, runway surveillance, and aircraft maintenance. Computer vision systems can identify and track objects, such as aircraft, baggage, and people, in real-time, enabling airports to manage operations more efficiently.

According to a report by Mordor Intelligence, the use of computer vision technology in airport operations is expected to grow at a CAGR of 12.5% from 2020 to 2025. This growth is due to the need for enhanced safety measures and the increasing demand for operational efficiency in airport operations that can be achieved through use cases like object detection, automatic cargo count, passenger tracking, and more.

Passenger Tracking

Computer vision can track passenger movements in the aviation sector, detect and analyze passenger behavior, identify potential security risks, monitor crowd density, and optimize the passenger flow. It is commonly useful in security checkpoints, boarding gates, and baggage handling areas to enhance safety and improve efficiency.

Computer Vision Challenges and Potential Solutions for Aviation Industry

Despite the many benefits of computer vision in the aviation industry, there are also challenges associated with its implementation. One challenge is the need for extensive data processing capabilities. Computer vision systems require significant amounts of data processing to identify and analyze images accurately.

Another challenge is the need for effective integration of computer vision technology with existing systems. This integration of computer vision technology with other aviation systems can be complex and time-consuming.

Potential solutions to these challenges include the use of cloud-based systems that can handle large amounts of data efficiently. These systems can update and maintain remotely, reducing the need for regular maintenance.

Also Read:

Advanced Intelligent Traffic and Parking Management Systems

In conclusion, the statistics support the increasing use of computer vision technology in the aviation industry. This technology offers significant benefits, including increased operational efficiency, enhanced safety measures, and cost savings. However, the implementation of computer vision technology in the aviation industry also presents challenges, such as the need for extensive data processing capabilities and effective integration with existing systems. Hence, with careful planning and implementation, computer vision technology can revolutionize the aviation industry. This would lead to improved efficiency, safety, and productivity in airport operations, aircraft assembly, and maintenance.

Computer vision has indeed been influential in computerizing quality control due to its capability to locate, recognize, and examine product lines using algorithmic imaging techniques.

However, traditional algorithmic image processing has limitations that have typically restricted computer vision applications to component inspections. When the element is part of a bigger assembly, complex package, or kit, such as an automotive assembly, circuit board, or surgical kit, random product placement, lighting variations, as well as other variables can overpower the computations of traditional computer vision systems. As a result, final assembly, package, and kit inspection have remained largely a manual operation.

However, with the advent of technology and raised efficiency of computer vision, the entire process of manufacturing and its complex areas have been taken care of and entirely automated, part kitting being one of them.

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The Work Process of AI Integrated Kitting

Due to rising consumer demand and expectations, packaging and kitting companies require the highest levels of accuracy and efficiency. However, the most significant impact of packaging and kitting errors is the cost implication. For many businesses, the most damaging outcome is downtime. This manifests as both opportunity cost and the production of additional parts. In some cases, these costs can amount to millions of dollars per shift.

The kitting workstation now has a CCTV camera. Every possible “kit” has its anomaly model. A fixture is used to ensure that parts are in secure locations. By scanning a barcode on the kitting container, the operator tells the system which kit they are pulling for and the barcode indicates which kit is being built and what parts are to be expected.

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When parts are missing or incorrectly placed in the kit, an error message is sent to an HMI via Modbus TCP via a PLC to alert the operator to double-check their work. In this case, a model must be created for each possible kit variant, which, while technically possible, requires a large amount of data. Multiple regions of interest (ROIs) are used to simplify model building and provide better quality metrics, building on the basic implementation. Each area of the kitting fixture can have its ROI.

All this makes model construction easier. Every possible part variant must be trained on each Region of Interest. However, rather than having to build a model for each kit, kits can be created by selecting the relevant parts from each model. Furthermore, rather than simply indicating that the kit is incorrect, the specific part that is incorrect can be identified using a multi-ROI inspection.

Conclusion
Because demand for some consumer goods is declining, manufacturers are slowing production and reducing the number of operators on the floor. Many people believe that now is a good time to start prototyping to better solve this problem when they ramp up again. The inspection game has changed thanks to AI in industrial kitting.

Computer Vision is a subset of Artificial Intelligence (AI) that enables computers & systems to capture and interpret information from image & video data and take actions or make a recommendation based on the information. As AI helps systems to think, Computer Vision enables them to see, observe & interpret. Computer Vision Applications have a great impact on companies in all industries from retail to manufacturing, healthcare, automotive to logistics & agriculture.

Computer Vision is useful in almost all business processes in every sector. Here are 5 exciting computer vision applications different domains:

5. Computer Vision Applications for Inventory Management

Whether it comes to storage, placement & keeping track of goods that enter or leave a premise, manual inventory management can be daunting. Businesses are deploying computer vision-based AI systems for efficient inventory management, which can perform every task without human intervention. AI cameras can count, detect & track different objects moving around space. AI-powered systems can track goods & their movements on every rack, identify empty spaces, make a note of goods running out, spot misplaced items and send alerts to managers in real-time, ensuring quick & systematic action. Also, you can analyze the consumption pattern of goods, identify fast moving goods & goods that are rarely consumed, helping the managers make insight-based procurement. All this prevents stock obsolescence, order cancellations due to insufficient stock, and pilferage that helps in efficient inventory management.

4. Pose Estimation using Computer Vision

   

Human pose estimation is one of the most exciting use case that represents person’s position in a graphical format. This computer vision technology helps in predicting a person’s body parts or joint position. With this technology, a computer can now recognize actions and inactions more accurately by performing pose detection & pose tracking. Human pose estimation technology has the groundwork in the areas of applications like sports & fitness, rehabilitation, augmented reality, health & safety, gaming, robotics, and even surveillance. Using computer vision, it can help in tracking the movement of a human body in real-time to split exercises accordingly, recognize activity for real-time sports analysis, enable more ways for physiotherapy treatment, better-augmented reality experience & in the animation of game characters. AI model-based technique can be used to represent and infer human body poses in 2D & 3D space.

3. Leveraging Social distancing Solution

Social distancing has not just proven to be the most useful & effective measure to slow down the spread of Covid-19, but is also an effectual way for ensuring employee productivity and security in certain industries. To ensure social distancing protocol in public places & workplaces, computer vision-based systems can monitor the number of people on premises. Find out if employees are keeping a safe distance from each other by analyzing real-time video. A computer vision-based social distancing tool is a combination of object detection & tracking in real-time. This tool enables person detection and tracking using bounding boxes. Bounding box analysis helps in detecting in real-time any violation of social distancing norm. This tool can integrate into the existing CCTV systems to monitor safe distance and trigger real-time alerts in case of deviation from the standard protocol.

2. Computer Vision Applications in Insurance

Computer Vision plays an imperative role within the insurance industry’s information technology systems. Since insurance is always data-based, it has the potential to be impacted by AI. The technology enables better underwriting & smoother claims process, which ultimately improve the customer experience. It also allows faster claims process by letting technology perform damage assessments using pictures, rather than in-person appraisals. With computer vision technology, policies can be priced more accurately & efficiently, also claims can be settled in a timelier manner. Computer vision-powered image recognition can speed up the insurance appraisal process. That’s not it, AI enabled drones cameras can shoot real HD video or imagery for visual inspection of damaged property. All in all, computer vision technology helps reduce claim settlement time, validate claims in real-time, improves appraisal accuracy & reduces fraudulent claims.

1. Automated Safety and Security Standards

While manual surveillance is effective, it is limited to personal capabilities. A security person can only watch surveillance footage that is restricted in both, time and degree of precision. Manufacturing workers are always working at risk of injury or death. Manufacturing facilities not complying with safety standards not only hold increased worker safety risk but also bear an additional cost.

Computer vision that provides higher accuracy and efficiency can be a great solution to overcome these challenges. The systems using this technology can monitor production site in real-time and send instant alerts in case of violations. With computer vision-based systems, manufacturing units can ensure safety and security standards for the employees. Even in the case of an active accident, computer vision enabled CCTV cameras can immediately alert where the accident occurred & what is the intensity. Using a computer vision system for social distancing detection, PPE compliance, facial recognition, intrusion & weapon detection, theft & fraud prevention, and crowd disaster prevention are some other applications for ensuring safety & security standards in a workplace.

Embrace the Technology

These are countless examples of computer vision applications in different businesses and industry sectors. The main feature of computer vision is high accuracy with which it can replace human vision when trained properly. Computer vision benefits list is unending- increased precision, automation, higher productivity, more efficiency, reduced cost and more. Different sectors are eager to explore computer vision technology and implement tech advancements to improve their business operations. Now is the time that we join hands to welcome computer vision and other AI-based technologies seamlessly to our business world for the collective betterment of human life.

Artificial Intelligence and Machine Learning are already here. How they are transforming businesses every day?

You probably interact with Artificial Intelligence and Machine Learning in daily life and don’t even realize it. AI has become a commonplace in our daily lives and is developing every day. AI is now a household name and sometimes even a household presence (hi, Siri!). Artificial Intelligence and Machine Learning are technologies that use machines to imitate human intelligence. It indeed has the potential to transform the way business operates. AI helps businesses to find solutions to complex problems with automated processes.

In business, AI has a different range of uses. From mundane to breathtaking, AI is already affecting every business process across every industry.

AI in Manufacturing

The use of AI in manufacturing has the potential to take the industry to a new level of productivity and profitability. Manufacturers can reduce their operational costs through intelligent automation & optimization, while also adapting to changing market conditions. Automation has taken up many manufacturing tasks and processes already and experts believe the remaining will be automated partially or entirely in the upcoming years.

AI in Healthcare

The use of AI in healthcare has been for a long time. Initially, it was mainly used for data analysis and pattern recognition. But now AI is transforming the healthcare sector with its new use cases. Some of them include medical imaging, remote monitoring, decision support system, and data mining. Patients’ vitals can be monitored with AI techniques like machine learning & deep learning. The data then helps in making decisions about patients’ treatment in hospitals.

AI in Logistics

Logistics is the backbone of any business, without which no business can survive. When it comes to AI transforming logistics the most important thing is to adapt quickly & efficiently to changes in demand using automation. The use of machine learning & predictive analytics has already transformed logistics, & making it a seamless sector. Warehouses are becoming ‘Smart’ through AI & ML technology for improved productivity, more efficiency, and high accuracy.

AI in Retail

Being the most competitive space, the retail organization always lookout for new techniques for giving a better customer experience and outsmarting their competitors. AI helps to find patterns in consumer behavior and thereby aligns strategy for enhanced customer experience. The shopping experience for the end users has been completely transformed with AI & ML technology. From using computer vision to customize tracking in real-time to applying machine learning for managing inventory, retailers can utilize AI to operate efficiently.

AI in the Banking Industry

With the onset of AI applications, the banking industry is undergoing a massive transformation. AI has plenty of use cases in banks & financial institutions. AI has helped to automate routine tasks for employees, letting them focus on more complicated problems. The finance sector relies heavily on AI & ML-powered systems to detect fraudulent transactions and pave the way for safer and secure transactions. AI in the banking sector automates complex processes, detects theft in ATMs, studies customer behavior, reduces paperwork, and gives a better customer experience, it saves time, resources, and money.

AI in Traffic Management

The fast-growing human population and increase in the number of vehicles on the road lead to issues related to transport & traffic. New AI applications that emerge in the area of transportation management have the capacity to transform traffic control. The technology is converting the traditional systems of transport management into Advanced Intelligent Traffic and parking management systems. Technology helps in designing integrated roadways based on smart systems.

The Future of Technology in Business

How might artificial intelligence affect business in the future? Well, it’s hard to say how technology will develop, but expert says it will keep making business tasks even easier.

AI is a blessing for your business; you only need a little imagination and creativity to use AI in the way to get the most out of it.

And if you want to unlock the power of a new business era with AI & ML solutions, reach out to Assert AI and talk to our experts. We will help you to get best the solutions.

Aiming to scale your startup but hesitate to adopt AI-based practices? Read This!

Artificial Intelligence (AI) is a buzzword in the tech industry; it’s a big innovation that your start-up needs to prepare itself for. There is a whole slew of opportunities in AI for Start-up business that can help in steady business growth. But it is typical for a huge innovation like AI to scare off a start-up because it seems a complex technology to implement. Being a start-up founder, adopting AI can help to scale your business.

With AI-powered solutions, you can go one step ahead of your competition & introduce your business to a new path of innovation & efficiency.
Artificial intelligence is the science for making your business smart. Not only big companies but both small companies & start-ups can harness AI to their advantage. With AI-powered solutions, you can efficiently yet creatively solve business problems & take your early startup to new levels of success & growth.

As per Statista, ‘the global AI software market will grow rapidly to $126 billion by 2025’.

This clearly shows that AI technology is here to stay & with an increase in the number of AI applications it’s gaining popularity every day. The corporations will continue investing in smart solutions to aid their business operations. And it is important to understand the growing demand for AI for any startup to stay in the competition.

The various opportunities in AI for Start-up can help you to leverage some amazing & practical services powered by the latest AI algorithms into your business. If you can implement AI use cases into your operations, it will surely take your business up by a notch. Here is how you can use AI for your business!
 

Startups can use AI to-

• Boost Productivity in the workplace
• Track down competition without incurring high costs
• Consolidate & boost marketing & sales operations
• Build a brand name & support customer loyalty by giving a better customer experience
• Streamline recruitment activities to find the best talent
• Make better, more efficient business decisions

Get a step ahead with AI!

The concept of startup growth is difficult to master but incorporating AI into your business can bring a great change. It can bring great returns for your company by simplifying, automating & improving your operations. By adopting intelligent solutions for your team and automating almost all critical business operations, you & your team can easily focus on major competencies, letting the digital system handle the rest. Needless to say, it works!

While many startups have already started embracing AI technology, others are still hesitant to make the move. But the early you adopt it, the more competitive advantage you can get. The future belongs to innovation, & with the increasing speed, of revolution you cannot afford to lose time.

Want to know how AI-powered technology can aid your startup with its various use cases? Get in touch assertai.com & take advantage of the most trending technologies.

In this erratic & unpredictable economic climate, it is crucial to increase warehouse productivity as much as its critical to reduce warehouse costs. Maximizing business profits takes a well-planned strategy as the competition is high. Reducing the warehouse cost is essential for survival but at the same time, it is important to maintain the quality & customer service.

Warehouse cost differs on the bases of the facility type, storage space & services provided. The major warehouse costs include handling of inventory, operations management, and general management expenses. The efficient management of the warehouse is the pulse of a supply chain. Warehouses are facing increasing challenges of labor shortages, pandemic issues, and changing market conditions, making warehouse management a complex task.

How to Reduce Warehouse Costs?

Reducing the costs is one of the most important aspects to manage a warehouse successfully. Several factors help to reduce overall warehouse costs. The most important among them are:

• Reduce required space by optimizing storage
• Protect inventory by efficient inventory control
• Reduce labor costs by effective workforce management
• Reduce equipment cost by proper use of equipment

To help in successfully performing all these operations, companies need to embrace the digital revolution to ensure their business thrives and not just strives. Organizations need to focus on strengthening supply chain & logistics capacity, thus reducing warehouse costs. Leveraging AI for warehouse operations can be an effective way of doing that. Technology is the main factor controlling warehouse costs. An AI-based warehouse has several automated systems that improve efficiency, reduce errors, and save money. One of the many technologies in the field of AI is machine learning, which is the core of data analytics algorithms that power smart and modern warehouses. When used properly, machine learning in warehouse management can help in scalability & cost saving.

“According to McKinsey, logistics companies will be generating $1.3-$2 trillion per year for the next 20 years in economic value by leveraging AI into their processes”There are different ways in which technology can work to optimize your business. It is time to use a dedicated warehouse management system for your business if you are not already using one. Here are some ways AI can improve warehouse operations & help in cost reduction of warehouses:

Storage Optimization

Efficient use of space is a critical issue in warehousing today. Poorly planned warehouse layout is a cause of plenty of warehouse accidents. Insufficient storage space or inefficient use of available spaces is the common problems of warehouses with a poor layout.

Automated systems like empty space detection show the floor & vertical space available for use. Also, object detection & tracking ensures the highest-selling inventory is easily accessible. Employing forklifts allows maximum utilization of available space.

Inventory Accuracy

Inventory in a warehouse should always be stored in properly identified areas. Accuracy & efficiency in handling inventory can lead to problems such as maintaining improper stock levels & build-ups of obsolete inventory. Lowered productivity, increased expenses & lost revenue are other impacts of inaccurate inventory.

AI-based automated systems like object detection, automatic packet counting, Bar code reading, logo detection, etc., offer real-time, accurate information about stock levels & compositions. Employing technology in inventory management can improve accuracy & reduce cost & time. RFID portals installed at strategic points automatically identify & track inventory as it enters & exits the warehouse, making it easier to locate a specific product, thus reducing costs due to lost or misplaced goods.

Labor Cost

An excellent warehouse manager is expected to increase productivity while minimizing labor costs. It is a balancing act for many warehouse managers. Generally, warehouses use expensive equipment & employ large labor forces from cleaners & packers to managers & administrators.

AI-based solutions are the lower-cost alternatives to human labor. AI can automate labor-intensive processes, thus reducing labor costs while improving quality. Automated systems can take on repetitive manual tasks ensuring that employees can focus on more important strategic tasks.

Preventive Maintenance to Reduce Warehouse Costs

Preventive maintenance is the prediction of potential machine failures in the factory by analyzing real-time data. Material degradation or corrosion is a very common problem for manufacturing processes that happen at the special temperature & environmental conditions. The result of this is the deformation of equipment. If not identified early, this can lead to major losses. For this reason, preventive maintenance is used for equipment monitoring.

Preventive maintenance is condition-based maintenance that monitors the equipment using sensor devices. These sensor systems provide data in real-time, which helps in making predictions when an asset requires maintenance, thus preventing equipment failure. Computer vision monitors equipment constantly based on different metrics. In case of any deviation from metrics, the sensors send an alert instantly to carry out maintenance activities.

Curb Theft & Loss for Cost Reduction

Another way in which AI can ensure smooth warehouse operations with reduced cost is by ensuring security & preventing loss. A warehouse is a large space & keeping track of every activity manually is a time & money-consuming task. Several AI-based solutions can ensure improved security & employee safety.

Automatic Number Plate Recognition (ANPR) system can track the authorized & unauthorized vehicle that enters or exits the premises in real-time and send instant alerts in case of intrusions.

Theft by humans within the premises can be controlled through Facial Recognition, Biometric Systems or Cross Line Detection. These systems can identify & track authorized employees in real-time. AI-based fire sensors can help to save a lot in content and structural damage by identifying fires at an early stage.

AI-technology systems help in intrusion detection to automatically identify any dangerous situation. Computer vision-based systems allow people to count and detect anomalies in movements, and crowd behavior analysis in real-time.

Final Words

Identify where & what type of cost-reducing measures is required the most in your set-up. AI is rapidly affecting the way modern warehouses perform their day-to-day operations & make long-term strategies. An integrated warehouse management system (WMS) can significantly be beneficial for your business to reach the desired objectives. AI-based intelligent warehouse solutions are helping organizations to improve operations & reduce costs by creating more efficient, flexible, and faster systems.

Want to improve warehousing operations & reduce warehousing costs without sacrificing the quality? Contact our experts & learn how you can run a more efficient & sustainable warehouse by leveraging our AI-based solutions into your present infrastructure.

Advanced Intelligent Traffic and Parking Management Systems

Stock markets might plummet and climb, companies may announce layoffs and triple the headcounts, lockdowns get imposed and lifted, but what shows a steep rise in the charts are the growth in the number of vehicles thereby leading to ever-increasing traffic. Traffic and Parking Management Systems looks like the only viable solution at hand and it is looking more and more promising by the day. In the wake of traffic control experiments like baricading, U-turn prohibition, multi-laning, flyovers and paradoxically, Odd-Even failure, it’s time we turn to advanced technology eventually. All we need is a system to manage the traffic on roads & in parking spots effectively. This can be achieved through automation that comes with Machine Learning (ML) & Artificial Intelligence (AL) algorithms.

Artificial Intelligence is the biggest innovation of computer science in this emerging era of big data. It is one of the new terms in the field of technology and has is predicted to solve so many problems. AI is making amazing progress, especially in data mining, machine learning, computer vision, natural language processing, robotics, and other related applications.

ML and AI in Traffic and Parking Management Systems

ML and AI train your systems to learn & make decisions similar to humans. AI is present in every area of our daily lives, from using social media to getting driving directions, voice control system to facial recognition lock in devices. AI is a revolutionary part of computer science, which is becoming the main component of our daily lives. It can imitate many human functions like recognition, speech, planning, learning & problem solving. The main motive of this technology is to overcome the prime barrier of Human Intelligence- Speed and Expandability. There is always a limit to the speed with which humans can perform tasks as compared to Machines. AI is overcoming this challenge by transferring Human intelligence to machines having exceptional capabilities.

AI is being developed and applied in wide range of sectors around the globe. Recently, its application has emerged in the area of transportation engineering, especially in Traffic & Parking Management systems. AI-based video analytics is converting the traditional systems transport management in to Advanced Intelligent Traffic and parking management systems.

Modern advancements in urbanization & a rising dependence on transport have lead to increase in number of vehicles on the roads, which has a negative impact on the quality of life. Increase in cars means less space on roads. This is not only a problem for roads but also for parking spaces.

Transportation issues Faced by an Average Citizen

Here are some of the challenges faced by an average citizen while driving their cars through crowded roads:

• Increase in number of vehicles results in little or no parking space
• Congestion leading to high fuel consumption & increased air pollution which is hazardous for life
• Time, energy & resource wastage
• Traffic jams resulting in increased travel-time
• Breaking traffic laws resulting in increased road accidents
• Inefficient parking skills resulting in poor space utilization

So what’s the solution?

Like every other sector, we need innovative solutions and this is where automation in traffic & parking system plays the pivotal role. AI-based smart traffic & parking system is the most innovative solutions to all the problems. AI-based solutions help in creating “Smart Cities”. AI-enabled software leveraged in the road infrastructure enables smart roads with automated transportation system.

Smart Roads

Artificial Intelligence (AI) technologies helps in designing integrated roadways based on smart systems. Smart roads help in improving road safety & reducing delays in traffic. The use of Internet of Technology (IOT) systems make driving safer, efficient & in-line with government objectives. Smart Roads are the combination of physical infrastructure like sensors & solar panels, and software infrastructure like AI & IOT. Sensors and smart cameras are embedded on roads, turning them into digital networks. Different technologies that enable smart roads are IP CCTV systems, speed sensors, smart traffic lights, and weather monitoring systems. These devices collects data automatically and analyze it in real-time. They can analyze traffic conditions and warn drivers about traffic jams, also prepare for emergency conditions like snowfall or floods, road construction and maintenance, thus reducing risk of dangerous situations in advance.

AI for Advanced Intelligent Traffic & Parking Management System Traffic Automation System

Using artificial intelligence in an open space like roads is possible by installing AI enabled smart traffic solutions within the infrastructure before launching self-driven vehicles. This system will consist of features like AI-enabled CCTV cameras that can capture drivers & commuters breaking laws, and automated number plate recognition (ANPR) cameras for generating e-challans sent electronically to violators. Intelligent traffic management system (ITMS) can facilitate a convenient, smooth & safer road experience for drivers by improving traffic management.

“Intelligent traffic management system market forecasted to reach around 18.7 billion by 2028- Report by Market Research Future (MRFR)”

Parking Automation System

AI-based smart parking system is an important part for parking management, being beneficial to both parking users & parking managers. AI-based sensors used to analyze parking vacancy help in more efficient parking management. The Intelligent parking management system works on constant real-time data collection. The system helps to make the process of car parking more efficient & less complex.

Let’s check out the most popular AI applications in transportation:
Automated Number Plate Recognition (ANPR)

The ANPR system is one the AI-based smart system solution. It uses the optical character recognition technique. The system uses ANPR cameras to scan & read vehicle number plates both during day & night. AI-based ANPR system helps both in traffic & parking management system. The AI-based parking sensor system identifies a vehicle & grants automatic access, eliminating the need of pressing button or getting a parking ticket etc. This makes vehicle entry/exit flow faster & improves parking experience. Parking managers can have easy access to parking occupants and decide who can enter & when.The ANPR system on roads helps in easy vehicle identification in case of any traffic rule violation. ANPR is used to monitor the average speed of vehicle & identify vehicle that exceed the limit.

AI-based real time data can generate real-time alerts. It can automatically challan the offenders & send e-challan electronically to the violators. The ANPR system can also help in vehicle detection in case of hit & run accident cases & also helps to spot out stolen vehicles. It is a very efficient tool for toiling systems. ANPR helps to improve the vehicle mobility & traffic safety.

“ANPR cameras have recently been installed in Vellore district border check posts to auto-detect offenders. The cameras will capture the number plates and will analyse data the system has already been trained for. The data has black-listed vehicles, that have been stolen. If a passing vehicle is found to be black-listed, the ANPR cameras will alert the police.”

Real-time parking vacancy

AI-based smart parking systems include special tools that can perform real-time count of the number of parked vehicles & empty spaces in a parking lot. There is a common problem of too many vehicles & not enough parking spaces. But the AI-based parking solutions can provide real-time data about parking occupancy & vacancy, helping parking users to find where to park. This in turn helps in solving the biggest problems like circling for an empty space and city traffic. Parking managers can analyze real-time data to optimize current parking management strategies accordingly.

“According to GlobalNeswire, a study recently conducted by the strategic consulting & market research company BlueWeave consulting revealed the global smart parking systems market was worth USD 4.5 billion in 2020 and is further projected to reach USD 17.2 billion by 2027, at a CAGR of 21,2% during the forecast period (2021-2027).”

Smart Traffic signals

Traditional traffic lights change colour depending on the predetermined rules & inductive loop sensors embedded in the road. This predetermined traffic light system itself might be correct, but the humans working behind aren’t perfect always. Mistakes occur at the back end, and sometimes drivers run a red signal and thus accidents occur. However making these lights intelligent using AI technology can maintain faster & smoother traffic flow. AI based cameras record data like number of vehicles waiting at the signal, vehicles waiting time, and vehicles speed at intersection. The collected data helps to train deep learning algorithm. The system then virtually experiments with different patterns, continuously adapting to real-time traffic conditions to minimize the wait time. AI embedded sensors on signals can also detect & identify vehicles that run a red light & send instant real-time alerts to concerned authority.

“The Gurugram Metropolitan Development Authority (GMDA) is working on a project to convert 90 traffic signals in the city to smart signals using adaptive traffic control systems to ease traffic flow in the city, as per Hindustan Times”

Traffic flow analysis

The flow of traffic impacts road safety. It somehow also impacts a country’s economy, both for the better and worse. Road congestion leads to money & time loss, causes stress to the commuters & drivers. With a better traffic flow the safety of road users can improve immensely. Artificial Intelligence is now helping for better traffic flow management using computer vision systems. With the help of computer vision, drone & real-time camera sensors based traffic flow analysis is now possible. AI solutions help in reducing congestion and eliminating choke-points that clog up the roads. The AI-based algorithms can track & count freeway traffic accurately and analyse traffic density. This helps traffic managers to understand and design more efficient traffic management systems, thus improving the road safety.
If that isn’t enough, AI sensors can even predict hazardous events, and provide real-time insights of peak hours. By using this real-time data, traffic managers can greatly reduce the traffic congestion & improve traffic flow.

Road Condition Tracking

Damaged roads & potholes is a major issue affecting the road safety. Traditionally, road condition tracking has been a manual errand to give a heads up to the traffic managers. But AI systems in transportation can detect damage successfully in real-time. AI-based computer vision algorithms can identify potholes & analyse road condition so that the relevant authorities can initiate road maintenance. AI systems will update damage in real-time with no human intervention for quick action. This will ultimately save time & money, and improve road safety thus reducing the accidents.

Final Verdict

With the revolution of AI technology, the future of Advanced Intelligent Traffic and Parking Management Systems is becoming brighter. This technology is making everyday life of citizens more comfortable & safe, and also providing real-time solutions to everyday traffic problems. With highly optimized management system AI is paving its way to build every city a Smart City.

We’re living in 2022 and Automation has become the buzzword across all sectors and industries. Warehouse automation, in particular is the process of automating the warehouse security, inventory management, workflow, health & safety compliance and a lot more with minimal human intervention. Remotely manage AI powered warehouses and eliminate repetitive labor-intensive work, manual data capturing & analysis as well as critical tasks with zero tolerance for error.
Warehouse Automation is primarily possible with two different perspectives- Physical Automation and Digital Automation.

Physical Warehouse Automation through Warehouse Automation Equipment

Use AI powered video analytics for tracking employee movement, build an efficient workflow, improve warehouse capacity, boost efficiency, reliability & scalability and improve overall performance in multiple ways. Use of technology for more hazardous or time consuming tasks helps employees stays safe while performing task in coordination with fully automated equipment monitored remotely.

Digital Warehouse Automation through Warehouse Management System (WMS)

Digital Automation is the use of data & software in warehouse while reducing manual workflows and automating the processes. AI for warehouse management deployed for monitoring, inspection & analysis of warehouse processes is one common example of digital automation. You can get plenty of AI automation examples and benefits for warehousing including enhanced safety & security, increased data management efficiency, optimized ERP systems, reduced operational risks, and reduced human errors. The list is pretty long and LinkedIn articles have a word limit!

Why and How did Automation Become the Next Big Thing in Warehousing?

From poor layouts and inventory inaccuracy to accidents and human errors delaying deliveries to redundant process and varied labour requirements and cost, there are many challenges faced by warehousing, logistics and supply chains. All these require automated system solutions to keep managers aware of gaps that require attention.

Due to globalization of markets & increased global diversity of goods, warehouse systems are becoming more complex & challenging. This leads to the increasing demand for automation & digitalization of warehousing and related processes. Technology is progressing at a rapid pace in all sectors of industries. To monetize on the latest developments, warehouses have started adopting new technologies that help them to be aligned with manufacturing, production, and consumer demand. Warehouses are becoming ‘Smart’ through automation for improved productivity, more efficiency, and high accuracy.

How Computer Vision works for Warehouse Digitization

To remotely manage AI powered warehouses, the use of computer vision is most widespread and hence AI-based video analytics is the emerging technology in this sphere. Computer vision based image and video processing and analytics help the efficient handling & flow of goods. Video analytics solutions are based on three aspects- Capture, Analyze & Insights.

How Computer Vision systems actually works:

1. Camera captures the image or video
2. Deep learning techniques analyze the visuals
3. AI generates Insights to automate specific tasks

Further in this article, you will get an overview of the emerging trends of computer vision & image and video processing for warehousing, logistics & supply chains.

Top applications and use cases of Computer Vision in Warehouse Management

Let’s discuss the most trending computer vision applications & use cases for warehousing in detail.

Traceability, Tracking and Counting of Objects

Use of smart tracing helps identify different objects such as inventory, containers, persons, or vehicles within or outside the warehouse. This is mainly achieved by building an object detection system using Machine Learning & then using computer vision to capture & identify items. These systems are used to identify flow of goods in warehouses. Camera-based systems are also used for automatic packet counting to get real-time accurate inventory data. In warehouse processing, optical character recognition (OCR) systems carry out real-time identification of container codes & automatic number plate recognition. Visual container recognition is completely contactless, thus making the tracking of containers of different parties efficient.

Automated Quality Control

Quality check systems in warehouses currently rely on visual and manual inspections. Automating these visual inspections ensures accuracy, efficiency, and helps in better quality control. Video analytics has many use cases in warehouses to ensure quality control. AI-based vision cameras are also leveraged in both manufacturing & packing processes of goods. Using a set of AI vision technology warehouse managers ensures quality control by automatically detecting product defects on incoming parcels or containers. Visual documentation, monitoring and real time event detection ensures integrity of goods. AI based camera systems can also automatically detect oddity on packages.

Predictive Maintenance

Equipment degradation or corrosion is a very common problem for warehousing processes resulting in equipment failure, and ultimately downtime. If not identified early, this can lead to major losses. For this reason, predictive maintenance is used for equipment monitoring.

Predictive maintenance is a condition-based maintenance that monitors the equipment using computer vision. Video analytics provide data in real-time, which helps in predicting when an asset will require maintenance, thus preventing equipment failure. Computer vision monitors equipment constantly based on different metrics. If any deviation from metrics is found, the system triggers an alert instantly to carry out maintenance activities proactively.

Storage Enhancement & Traffic Control

Efficient use of storage space is a critical issue in warehousing since time immemorial. Poorly planned warehouse layout is not only the reason for often-felt space shortage but is also a major cause for plenty of warehouse accidents. Availability of areas is important for efficient storage & transportation processes. Warehouse Video Surveillance Solution for your storage facility helps in monitoring space occupancy and availability. Automated systems like empty space detection shows the floor & vertical space available for use. AI-based cameras also detect specific parking places occupied by vehicles and register their number plate. This technology helps in dock utilization by monitoring the occupancy of docks. Cameras implemented in the vehicles or outside the gates helps in monitoring the loading conditions & available space thus optimizing the operating cost & improving efficiency.

Safety of Employees & Protection of Infrastructure

Workforce & Infrastructure are two bases for any warehouse processing. It is critically important to protect them both from any external or internal threat such as fire, accidents, theft, terror attacks, and God forbid, what not.

According to International Labour Organization, Worldwide, about 340 million work-related accidents happen yearly.

Even though cameras are installed in warehouses to monitor employee movement or any danger, but it is still largely a manual process where any employee needs to sit and constantly monitor the screen.

An AI-based computer vision system is the solution to avoid human errors. Deep learning algorithms help in intrusion detection to automatically identify any dangerous situation. Computer vision based systems allows people counting, detecting PPE kits, safety vest and helmets, detecting anomalies in movements, crowd behaviour analysis in real-time and remotely manage AI powered warehouses. AI-based ANPR systems monitor entry & exit of vehicles to ensure maximum safety and better management. Fire & smoke detectors leveraged with AI technology sends early warning to hotspots that are detected. These cameras can be used to save a lot of collateral damage by identifying fires at an early stage.

In case of any accident, AI-based video analytics systems can send early alerts to managers & employees about the accident spot & the intensity of the accident, so that proactive measures are taken to ensure safety of employees.

Facial Recognition

Facial recognition can play an important role in on-site security process. Warehouses usually store high value goods & resources that require efficient monitoring & restricted access to only authorized people. Deploying facial recognition system improves security. AI-based facial recognition system identifies employees, carries out employee attendance, authorized access control, and block-listed persons. Not only it maintains detailed logs, but also sends instant alerts to security personnel whenever required. Check-in/out process can be automated by placing AI-powered cameras at entrances.

These systems are 100% automated, eliminating the need of manual monitoring by security staff by sitting & watching multiple monitors, thus freeing them to respond any alert quickly. Facial recognition systems can maintains data to ensure that only authorized personnel is operating resources & equipment, and accesses restricted areas. The systems sends automatic alerts if someone violates any safety standards.

Monitoring handling systems

Monitoring handling systems include handling, loading, picking, and sorting operations for both manual & automated systems within a warehouse. Manual handling systems refers to use of manual labour for the process of moving & handling materials, while automated handling systems use technology for handling & carrying out processes. Automated handling systems ensure inventory accuracy & quality control by identifying & analyzing small or fragile inventory for better inventory control. AI-powered cameras can identify items during the process of loading & unloading while goods are on conveyor or forklifts or even handled manually. Automated material handling helps in increased warehouse capacity & efficiency, enhanced reliability, scalability of services, and improves performances. Warehouses using computer vision technology can deploy video analytics systems in order fulfilment for receiving, picking, packing, and shipping of goods. These systems also send instant alerts in case of any mishandling of goods such as throwing or dragging of goods, sitting on goods etc.

AI powered Drones for Warehouse Management

protecting it against any kind of intrusion by detecting people, vehicles and even animals. All the process is carried out in real-time without any human intervention. Drones can be deployed easily, without hindering any warehouse infrastructure. Drone adoption by warehouses improves data integrity & operational safety, thus improving processes such as cycle counting frequency, on-time deliveries, worker safety, inventory accuracy, slot utilization, etc.

How to get started?

If you are looking for AI-based video analytics solutions to build computer vision applications in warehouses, check out computer vision platform assertai.com and remotely manage AI powered warehouses. Assert AI is a pre-eminent computer vision company in India offering high-precision, customizable AI algorithms to help you properly manage the system. Warehouse management system not only effectively ensures the compliance of various SOPs but also sends real-time alerts on human intrusion and fire or other hazardous incidents. Leveraging your existing infrastructure, AI algorithms can seamlessly connect to your cameras to automate the monitoring of your facility in real-time.