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6 MIN Read Thanks to the pandemic, businesses have witnessed transformation breakthroughs during the last two years that were to happen in the next 5 years. The technology adoption trend will continue to accelerate. It mainly consists of AI and intelligent industrial automation. Although businesses are still in the process of getting a firm grip over various AI […]
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How Accidents in Manufacturing Units Can Be Prevented Through Artificial Intelligence in CCTV Cameras
Innovations are changing the world rapidly. A tiny mistake can lead to a big disaster in today’s world, especially in some major sectors like manufacturing and logistics. This is because mainly these sectors require continuous human alertness to remain safe while working. That’s why workers in these areas have to stay more attentive to the changes happening in the workplace. However, human vision is liable to overlook small changes around them. In some situations, it can rise to a potential or a big disaster that can also risk human life because of small changes.
What is Artificial intelligence?
Artificial intelligence is known to be a compelling and valuable technology. People have gone to great lengths to add AI technology to their work. Every day, research has been conducted to know more about this and continue developing AI solutions that benefit everyone. Most people think that these technologies are removing the workforce, but it’s not true. These technologies are used by the people working in the industry. Through such innovations, we can create a safer workplace, help people, make processes more effective and efficient, find new and unique patterns, and prevent repetitive injuries.
How Humans and artificial intelligence are interlinked?
Suppose the task is highly repetitive and monotonous. In that case, it is best suited for Artificial intelligence to take over that task as such innovation have the high order thinking skills in comparison of human. This technology neither gets tired quickly nor gets fatigued can constantly look upon the industry can pre –detect if it feels something strange or weird. Talking about humans, we can’t entirely neglect them as they can perform other roles such as supervising, programming, and repairing technology that are performing repetitive or dangerous tasks.
How artificial intelligence in CCTV cameras helps in preventing accidents in manufacturing industries.
Artificial Intelligence has a significant role to play if we talk about the manufacturing industry. This technology helps the manufacturers prevent accidents that can cause risk to human life, run more innovative and significantly enhance the safety of operations. Wobot.ai artificial intelligence-powered solutions in manufacturing, specifically in significant sectors like chemicals, heavy machinery, and big assembly lines, helps to predict and look out for possible faults in equipment, any deviation from SOPs, assembly-line robots, and safety measures which can help in reducing the significant accidents.
CCTV cameras in the manufacturing industry can easily facilitate safety as they can quickly analyze data at a rate that’s impossible for humans to achieve.
Wobot AI-powered cameras in CCTV also analyze live feed with deep learning and give actionable insights and that too in real-time. With this solution, we, at Wobot.ai, aim to achieve zero accidents in manufacturing premises. Moreover, using this solution in promises will help create a virtual map to analyze the total; operational areas, define non-compliance and configure the types of alerts to be raised.
Globally, there is significant room for improvement in various aspects of safety. Past analysis has suggested that 40% of safety incidents can be attributed to injuries due to an oversight that can be easily prevented. Adopting Wobot AI-powered CCTV cameras, real-time data collection, and advanced analytics helps improve the safety of personnel & physical assets within a manufacturing environment. These technologies are highly promising regarding the benefits they can bring for safer operations through an ‘integrated safety compliance strategy.
The common cause of accidents in manufacturing industries is non –compliance, like people not wearing harnesses, working in unsafe areas or at heights, etc. Therefore, it is because of these reasons that non-compliance can be monitored through Wobot’s AI systems.
Through these CCTV cameras, supervisors can monitor how people perform inside the factory. Early indications can be provided if people are not following the regulations, which can send warnings or emails to managers and cut down improper practices, thereby improving the safety situation inside a factory
Can Artificial Intelligence in CCTV Cameras prevent 100 % of accidents in the manufacturing industry?
Talking about capabilities, then AI has more capabilities than humans. AI also has a prominent contribution to increasing safety in the manufacturing industry. There are many opinions that the industry can prevent 100 % zero accidents through AI. To achieve no casualties, the operator must also follow all the instructions and rules to blame Artificial Intelligence. Wobot’s AI systems combined with timely human intervention can maximize the levels of safety across the operations.
Conclusion
Through advancements in technologies, Wobot.ai is at the forefront of this technology because AI has a huge potential to drastically improve safety and increase the visibility of problems before they turn into crises. The focus should be on embracing these technologies and putting them to use. Industries must understand that AI requires a lot of coordination, planning, and insight before finding out an ideal solution that can reduce accidents inside the plant.
Role of VMS in the Corporate Sector to Comprehend Business Needs
The new age video management software are truly strategic investments that sometimes provides revenue generating options. Lot of investment is deployed and maintenance for Video Management Software, right VMS software always pays off in terms of managing and enhancing business operations along with innovative surveillance features.
Every enterprise needs robust VMS software to secure their assets and ensure continuous monitoring and surveillance and this is where Wobot.ai comes into play. Since every surveillance project is unique, the main challenge for any enterprise is selecting the right VMS which can help in fulfilling their business needs.
How to select the right VMS
The selection of the VMS depends upon the industry where VMS software should be installed. The architecture greatly depends on the industry for which it is being designed. The layout of VMS depends on industries that are unique in each case. Industries help in broadly defining the scope of the surveillance projects with the VMS system. The enterprise can decide on static, retail or dynamic.
Size of the Organization
The size of the organization is crucial to be able to decide the sheer scale of surveillance projects. Enterprise with reference to their surveillance projects sizes can be differentiated as small, medium and large VMS installations which help in predicting the scalability of the project with an exact number of surveillance cameras and devices required for the system.
Business Requirement
Business enterprises are tasked with overseeing the requirements of surveillance solutions i.e. the need for a new VMS or an upgradation of their existing VMS. Or an up gradation of their existing VMS. Both the scenarios are different.
There are options to choose from the available systems in the market.
When procuring the new VMS system, there are no additional costs incurred. Since cameras and devices are new, their compatibility and future requirements with the system should be monitored and assessed.
In case of an upgradation, the enterprise should look to VMS solutions that will amplify improvements. However, the primary challenge here is migrating from the legacy system of the existing network of cameras and connected devices. Hence, it is imperative to have a system that is compatible with the existing ones. Before acquiring the software, the organization can conduct a free VMS test to examine its effectiveness.
VMS takes a proactive approach to mitigate the risks. It gives the organisation the situational awareness of their security system through seamless integration of video and access control.
Types of Deployment
The type of VMS system that is adopted will depend on the nature and dynamics of the organization in question.
Single site or multi sites businesses require different deployment types of VMS systems.
VMS is categorized into premise, cloud based and hybrid based. The VMS system is further classified as small, medium or large size installation types. On the other hand, the cloud VMS services are adopted by most organizations owing to the many associated advantages.
Customisation is done as per requirements. Different options for VMS are systems available in the market. Therefore it is important to select the right vendor who can understand their business and support with the right customisation of the video surveillance solutions and pricing models to suit their business outcomes.
Types of Surveillance Cameras
Surveillance cameras are the sources of video feeds which are the most important assets in a video management system. Therefore they should be chosen with careful consideration.
The selection of surveillance cameras can be based on the types and features of the cameras which is for the user specific requirements of the surveillance sites.
Cameras chosen are based on resolution, night vision, field view, video analytics, inside /outside view, weather protection etc.
Integration with Connected Devices
Connection devices in VMS not only support advanced video surveillance but also help in generating useful data in improving business operations.
Connected devices in the VMS system include control devices, alarms, sensors, microphones, accelerometer, GPS devices, POS, traffic signals.
Important for the management to know potential vulnerabilities of their business operations and identify the sensors or devices to integrate to overcome the same.
Checking the possibilities of integrations of these devices in the system.
Video Analytics
Scope for utilising video analytics since it is a powerful medium to check on the fraudulent activities
Analyse the system effectiveness
Generate intelligent data to support business processes.
Result of functionalities of the connected entities or the algorithms specifically designed for the surveillance project.
Impact of certain decisions- like product placement, promotions, marketing etc.to get the right video analytics assistance.
Deploying Video VMS management software to analyse the requirement of the system - notification, responses, incident capture or identify the impact.
Video management software used in retail are queue management, face recognition, product placements, promotions.
Monitoring driver behaviour, vehicle tracking, fleet time management, harsh braking.
City surveillance video analytics - traffic management, tolls, smart parking systems, managing intelligent transport etc.
Future Scope of the Organisation
Selecting the expansion plans for selecting the free VMS Software.
Analyse the business forecasts and predict the possibilities of expansion of the infrastructure.
More enterprises required an efficient surveillance system to cater to their expanded items.
Enterprises grow with time- investing with system integrators and service providers to invest in the VMS system. It requires to stay updated and can be scalable as per future requirements.
A web /mobile application of video management software gives the freedom to access the entire system from anywhere, anytime and any device.
Cloud based video management system based on micro services and multi-tenant federated architecture, allows enterprise to scale to any no of cameras and surveillance sites.
Thus the role of VMS in the corporate sector to comprehend business needs cannot be denied.
Latest Computer Vision Technology Trends to Watch Out In 2021
The field of computer vision has advanced rapidly in recent years. Today, computer vision is one of the most promising areas in Artificial Intelligence and computer science. It is estimated to be USD 24.03 billion market by 2027 from USD 13.75 Billion in 2019, with a CAGR of 7.8% from 2020 to 2027. To pit it simply, computer vision trains digital system to process, interpret and understand the visual data (images or videos) in the same way human do. By using digital images and deep learning models, machines can recognize and classify-objects and react to them.
Before the onslaught of the golabal pandemic, the computer vision market was already on a trajectory of immense progress. However, the pandemic has served to accelerate this market growth multifold, with multiple industries adapting digital transformation overnight. The strides which would have been made in five years were achieved just in six months. Market reports have observed that this trend will continue in industrial automation and Artificial Intelligence throughout 2021. The present article aims to chart the top computer vision technology trend that the world will witness in 2021.
Computer Vision Technology Trend 1 : Ensuring Public and Work Place Safety
Covid - 19 has brought many unprecedented changes to the work place, and given such changes, There is a greater need for improved work place safety. The guidelines issued by the US agency, OSHA (Occupational Safety and Health Administration), necessitate the employers to protect their employees from workplace hazards that can result in illness or injury. The new safety protocols. HSE video anomaly detectors are being employed, effectively for automated monitoring and analysis to detect anomalies, such as failure to wear safety masks, PPE kits, or violation of social distancing norms, to ensure employee and work place safety.
Computer Vision Technology Trend 2 : Automated Anomaly Detection for Quality Assurance
The manufacturing industry spends precious hours on manual detection of manufacturing defects, and yet, it leave a margin for human error. Solutions such as computer vision technology tools specialize in elevating human inspections and quality control to mitigate potential human errors.
Computer vision technology has been adopted to automated PCB production monitoring and detection by one of the largest electronic manufactures in India. High-quality image data of printed circuit board (PCBs) can check for 20+ anomalies and defects. This market trend of automated anomaly detentions and optimizing visual inspections is also permeating other industry such as food and beverage, automotive, steel, ect.
Reduce workforce, declining profit margins will lead more industries to adopt computer vision and Artificial Intelligence powered inspections to attain quality standards with better accuracy and lower cost.
Computer Vision Technology Trend 3 : Thermal Imaging Analysis
Thermal imaging analysis is based on using light/heat energy signature to access the surroundings and is already in use in various fields. Military forces often use thermal cameras for night vision. With reduced pricing, the application is being opened up for use in other areas as well.
One such application is augmented not destructive testing Computer Vision. It accesses anomalies and identifies interest areas with a high probability of defects using radiology images taken through NDT techniques.
Automated Vision is based on inspections that increase the visible spectrum and detects the metal surface defects often invisible to the human eye. Recently, thermal imaging data has been utilized to understand hoe the rapid dwindling of the surface cover of the Peruvian Andes Glacier. Consequently, the surface area has been an increase in shrinking by 30%, which has impacted the melt rate. Such adverse development have posed severe threats to the water supply of the people inhabiting the Ancash region of Peru.
Computer Vision Technology Trend 4 : The Rise of Edge-Computing in Real-Time
Edge computing allows the data to be processed and analyzed at the point of collection itself instead of being carried out in the cloud or at the data center. Thus, It is attached to the physical machines and has proven highly beneficial for industries prone to network outages.
Technological prowess in edge computing promptly resolves issues regarding latency and network accessibility, resulting in a better real-time response. It allows the moving of only relevant insights to the cloud for further analysis.
In labor - intensive process, the software examines every steps of the manufacturing process and defects anomalies in real time with the help of Video Analytics. The recorded data provides a holistic view of the entire process. It saves hours of human labor and identifies bottlenecks in real time.
Video Analytics Software on edge is emerging as as visible option for business needs in 2021 with faster computation, real time insights, and high data security.
Computer Vision Technology Trend 5 : Helping Hands Through Sensor Data
Intuitive control interfaces, robust edge computing, and efficient closed loop information exchanges enhance sensor and vision data integration. Video Analytics has opened a new frontier for automated surveillance in defense. Video Analytics can automatically defects event and alert security forces that have contributed significantly to national security. Advanced perimeter monitoring system collect data - sensor data, video feeds, and drone imagery - from multiple location and monitor it to provide real time insights.
According to market research, the year 2021 will witness more advancements in the fields where more advanced capabilities will integrate machine learning based models and physics to explore and co-relate vision anomalies. This will generate actionable insights focusing on developing related frameworks and integrating data and asset monitoring with video insights. It will allow the supervisors to track anomalies, detected asset downtime, and implement plant safety.
Conclusion
Computer Vision Technology has emerged as a game - changer for many industries, Particularly Manufacturing. From Work Place Safety to its applications in quality control to its reliance in surveillance to edge-computing for better response in real-time, The Applications of computer vision technology has already been adopted by numerous companies with technology innovation underway and increasing flow of investment in the field, 2021 will be an excellent year for the growth of computer vision technology.
The advantages of offered by the computer vision technology will provide business an edge there competitors. Backed by the acceleration in digital transformation and amalgamation of computer vision technology with different technology.
Video Management Software For Market Growth and Future Prospects
A video management software is an essential element of the video surveillance system widely used for data collection and storage. It collects the video from cameras, records the video in a storage device, and provides an interface to view and record the live video to the user. VMS can be easily integrated with numerous third-party solutions and devices — fire alarms, video analytics, intrusion detection systems — to augment the efficiency of the surveillance system.
Video Management System with AI-powered Video Analytics
With the advent of technology, business enterprise have relied on prevalent monitoring mechanisms to track their operations, which involved close circuit television (CCTV) coverage of specific areas within their premises. Depending on the duration of the monitoring, the footage is usually substantial making it very difficult to analyze manually as it is a time-consuming process and at times the results are inaccurate. But gone are the days when this technology seemed to be somewhat adequate. Today, artificial intelligence has revolutionized this entire process of monitoring and analyzing every second of CCTV/video footage is much easier and faster. Wobot has introduced AI-based models for reducing the non-compliance risks of an organization. The software after getting installed in an existing CCTV camera can increase its monitoring capability to a great extent. The CCTV camera equipped with AI-based compliance can easily rectify all issues concerning surveillance, such as crowd analysis, safety risks monitoring, maintaining SOPs of a workplace, and much more. We have designed our advanced and intelligent system, considering the monitoring requirements in different industries including retail, manufacturing, hospitality and many others. The AI-based compliances offered by Wobot are acknowledged for their exceptional monitoring capability and easy setup. The Video Management Software with AI-Powered Video Analytics allows the user to access real time videos, record, store, & playback recorded videos and derive useful insights of the surveillance site. From a small coffee shop with four cameras or a big manufacturing facility with more than hundred cameras, Wobot's new-age VMS supports all business types & sizes.
Advantages of Merging Computer Vision with Checklists to Improve Compliance
The productivity and quality output of any organization depends to a large extent on its ability to ensure process and other regulatory compliance by the staff. There are standard operating procedures (SOPs) for different processes in an organization that the staff must abide by but it is a major challenge to ensure that with manual checklists. While 24/7 monitoring provides camera feed of employee behaviour at work, utilizing this footage to ensure compliance requires applications like video analytics and tools like computer vision. Integrating the checklists with computer vision will help in detecting non-compliance and flag it in quick time.
An organization has checklists for different process and safety compliances that the personnel working there must abide by. Today, most workplaces have installed Close Circuit Television (CCTV) cameras for remote monitoring of employee activities. This results in a huge database of camera feed that can reveal instances of non-compliance with process and safety checklists. As it requires regular and fast analysis of the feed to flag such issues and take corrective action, the checklists need to be merged with the computer vision of the camera feed. This is possible with Artificial Intelligence (AI), which helps a computer vision system to analyse the camera feed in real time.
The integration of computer vision with checklists will help in improving workplace safety and productivity as well as predictive maintenance of capital equipment among others.
Highly accurate analysis of camera feed
The human mind is creative and operates in different dimensions but it has a major drawback in analysing patterns consistently. AI-powered video analytics uses computer vision to analyse camera feed in real time and raise alarms for any break in the pattern. Computer vision analyses the entire data of the camera feed in pixels, which is not possible with manual analysis because the human mind can't process data at this scale and with such precision. Hence, analysis of images with computer vision is very accurate in flagging non-compliance of process and other checklists. A study by Bloomberg of restaurants that had functional video monitoring in place, revealed a 22% decrease in theft along with a rise in profit of 7%.
Much faster analysis of data
In functions involving pattern-intensive image analysis and verification, computer vision can deliver results much faster. The endless feed from remote-monitoring cameras require to be analysed at speed and scale to detect violation of checklists by the personnel in a workplace and deal with such situations in real time. In manufacturing units having expensive capital equipment and machinery, this kind of fast analysis is ideal for predictive maintenance of the equipment, leading to better productivity. It’s sheer waste of human intelligence and ingenuity if they are made to do mundane work that machines can do much faster and better.
Better cost control with high quality monitoring
High levels of process compliance is directly related to proportionately better levels of productivity. However, achieving higher levels of compliance is very difficult with manual analysis of remote monitoring camera feed. When computer vision is merged with checklists for different process and safety compliance manuals, AI-powered video analytics can be used to cover all the gaps in process compliance. This allows human resources to be assigned to more creative and cognitive functions that machines can’t do. Optimum utilization of resources is a prime factor for better cost control in any business.
Conclusion
In many ways computer vision can be said to have evolved as a way to enable machines to see images, process them and raise an alarm when necessary. When it comes to ensuring process compliance in workplaces across industries, it becomes very important for compliance checklists to be integrated with the computer vision. A computer can only recognize patterns within the data feed it gets, which is many times more focused than how humans analyse images. It is quite normal for humans to stray from the image and look at things far beyond the scope of the image and its analysis.
Computers process image-based data by analysing the pixels having numerous shapes and colours. These are then configured to recognize this kind of colour pattern as a specific object e.g., a car or a house. Powerful algorithms in the AI-powered video analytics are able to recognize any difference between the patterns of the image data that has been fed into the computer vision and the processing parameters configured in the software. Hence, when the specific compliance checklists are merged with computer vision, it can easily detect non-compliance with checklists.
Wobot.ai specialises in designing AI-powered video-analytics that can be used to integrate computer vision and checklists for process, safety and other compliances in workplaces. Wobot's AI-powered compliance checklists are customised for different workplaces having specific requirements their own.
How Artificial Intelligence is Revolutionizing Food Processing & Servicing Businesses
Food processing and servicing (FP&S) is an extremely important sector in any economy as it is directly related to the most important part of people's lives - food on the table. Over the years, there has been a gradual effort to make the process more efficient by reducing wastage, which is a major problem especially in FP&S plants that don't invest in advanced technology. Today, artificial intelligence (AI) is transforming process control and compliance across different industry sectors and the FP&S industry is one such industry where this is happening at a significant scale.
FP&S is a core sector industry that operates on scale
The industry was estimated to be around $550 billion in India in 2020 and around $2 trillion worldwide during the same time. The way this growth is impacting the FP&S industry is revolutionary because of the improvements it has brought in especially with regard to compliance at different levels of the FP&S chain. Beginning with handling and sorting of the raw material coming out of the farm to processing of the feedstock and maintenance of the machinery and equipment, every process is regulated by different levels of compliance. Since the FP&S industry is operationally intensive, compliance protocols need to be followed minutely for which AI-enabled processes are necessary.
Critical areas of FP&S that are adopting AI
As already mentioned, one major challenge that the FP&S industry faces is, prevention of wastage. In the United States, which is one of the most advanced industrial economies of the world, wastage in the FP&S industry is estimated to be well over 30% which accounted for over $161 billion in 2010. The best way to deal with this challenge is by investing in processes driven by next generation technologies like AI.
The critical areas of FP&S industry that are increasingly adopting AI are sorting of feedstock, food safety compliance, cleanliness and hygiene, product development and product packaging. The combined effect of AI adoption in the FP&S chain is responsible for increasing safety of food products to levels never imagined before.
In any industrial process, recognizing patterns consistently is extremely important and this is where human ability is much less effective as compared to machines. It is a persistent data-crunching process that can be done many times more effectively by machines than by humans. Today, AI-enabled processes are taking over most of the high-intensity operations in the FP&S industry.
Regulations, SOPs and Compliance in FP&S industry
The Food Safety And Standards Authority of India (FSSAI) has published a training manual for supervisors in the FP&S industry, where all the details of the food safety and hygiene practices to be followed by food business operators in India, has been provided. The food safety and standards regulations in this FSSAI manual covers everything from handling and processing of raw feed stock right up to the packaging and labelling of the processed food.
Beginning with laboratory and sampling analysis regulations it goes on to cover the required levels of health supplements, nutraceuticals, foods for medical and special dietary uses among others. It regulates the additives used in processed food and also ways to deal with contaminants, toxins and residues. It is a comprehensive document that covers almost every conceivable segment of the FP&S industry from the farm right up to the store shelf. AI-enabled video analytics can be used very effectively to supervise most or all of these processes.
Cleanliness and Hygiene Protocols Required in FP&H industry
Cleanliness in FP&S plants is not just cleanliness to the naked eye. The use of AI-enabled inspection has made it possible to identify impurities at the particulate level and get them cleaned up. The FSSAI manual clearly specifies the processes to be followed in cleaning up the plant including the frequency of cleaning, the procedure to be adopted and the equipment to be used along with the cleaning material as well as the method.
For instance, the equipment and containers used in the cleaning process should be made of corrosion-free material that are easy to clean and disinfect and doesn't leave any toxic particles on the equipment. The metallurgy of tanks, containers and pipelines should be of good quality stainless steel and not mild steel for optimum compliance with food safety regulations. Thereafter, use of multiple AI-enabled sensors to detect microbial food particles on the equipment can ensure compliance with cleanliness and hygiene norms.
Product innovation and development with customer feedback
Food manufacturers and retailers can move up from time-consuming surveys to measure customer preferences and automate the process at the POS. Thereafter, they can use AI to analyse the customer inputs and use it for development or re-development of products. For instance, a global soft drinks and beverage giant installed self-operated fluid dispensers at the POS and allowed customers to mix their own drink.
The results recorded and analysed by AI integration on the equipment, revealed data about the flavours that most customers preferred and helped the manufacturer come up with a newly blended drink. The FP&S industry is ideally placed to replicate similar customer engagement or devise unique methods to get insights about customer preferences with the help of AI. For this, they will have to innovate their processes and equipment at the POS and optimize them for AI integration.
Improving speed and quality in the packaging value chain
Packaging, which is a $900 billion industry worldwide is a critical segment of the FP&S process and AI-enabled tools are already improving processes like quality inspection, shelf-life timelines, etc. that also help improve the supply chain. One of the major risks of the food processing industry is food product recalls due to faulty packaging, labelling and end-of-line printing. In a large-scale packaging process, it is very difficult to ensure error-free output with manual inspection and analysis.
Such a process can be made many times more accurate, up to 100% with AI integration as it can read and detect fine print and other label text in real time and even flag errors simultaneously. This level of efficiency is not possible with manual inspection processes even at low intensity. AI can also make other complex packaging processes such as ‘make-ready’, related to plate-making, a lot simpler, faster and more accurate.
Improving process control in the FP&S sector is the biggest challenge facing the industry because it deals with massive wastage accounting for 30-40%. In this situation, investment in AI-based technology to improve process compliance especially in AI-enabled video monitoring is extremely important. Many organizations are already implementing AI integration in their processes and benefiting from it. The problem of wastage is also related to gaps in the supply chain management especially in procurement of raw feed stock from the farms, where a lot of wastage takes place.
Wobot.ai’s AI-powered platform provides the food services industry with specific checklists which can be used to ensure that process compliance is being followed diligently for proper waste management in the workplace as well as to ensure the safety and security of the employees and customers. Examples of such checklists include waste management checklist which includes monitoring of waste, garbage bins, garbage segregation, etc. This type of checklist can prove to be highly beneficial to the food services companies which deal with various challenges in dealing with waste and hygiene.
To check more about how Wobot.ai helps the food servicing industry, click here: https://wobot.ai/ai-in-food-hospitality-sector/
Using AI to transform the Video Monitoring world in real-time
In the last two decades, the world of monitoring has changed beyond recognition. The criminals are smarter now and have become virtually anonymous. The security threats unheard of in the nineties are now a reality. Human intelligence is limited, often flawed, and is incapable of dealing with security threats in real-time. Today, our cities have more cameras than ever before and yet the threats manage to slip through. The recorded footage has to be monitored by human resources which are costlier and time-consuming as well as limited in its capacity. With the advent of artificial intelligence, there is no need to manually sift through hours of video footage to catch a criminal or monitor activities in stores or offices. A camera backed by artificial intelligence can easily process every inch of security footage in real-time and red-flag the threats in time to save lives and resources. This blog will explore the impressive capabilities of AI in different industries that have proven to be highly beneficial for businesses around the world.
Artificial Intelligence for Safety and Security Operations With its self-learning capabilities, AI quickly learns to sift through a sea of data fed to it on a daily basis to recognize the normal behavioral patterns. Based on these data patterns and behavioral modulations, artificial intelligence can identify risky situations and thus, help in controlling them, before they escalate. AI can alarm the police in real-time, in cases of suspicious activities, like people loitering around in masks at night at a particular place continuously, or if there are any unrecognized items like briefcases.
One of India’s most reputed finance companies had deployed Wobot’s AI-enabled security system in their branches to detect intrusions at night, violation of entry restrictions in the strong room, suspicious activity like hand raise in case of burglary. One crucial checkpoint for the company was gun detection (if someone is pointing a gun at anyone in the branch). To prevent and reduce damage from gun-related crime, it was vital to have the data and tools to detect such suspicious activity. Wobot created an augmented gun detection dataset to notify and raise alarm in case of violation thus helping the finance company in managing the security of their branches without the need for human monitoring.
Around the world, the Singapore Government in collaboration with Accenture, developed an AI solution which helped in managing high crowd activity, crowd size estimation and object detection with 85% accuracy at SG50 celebrations.
A recent study, ‘Value of Data Seeing What Matters – A New Paradigm for Public Safety Powered by Responsible AI’ concluded “Integrating artificial intelligence and analytics with public safety’s current closed-circuit televisions can transform the ecosystem from reactive to proactive, reducing US crimes by about 81.7 million by 2040 and shielding approximately 76,000 mass shooting victims by 2040.”
Artificial Intelligence for Detecting and Preventing Fraud Stores, retail chains, offices, etc. are always wary of theft. If it’s an insider job, it becomes very difficult to catch the culprits. Physical monitoring with its limitations poses a significant security concern. According to the National Retail Federation, the inventory loss due to shoplifting, employee theft, or other errors and fraud resulted in the loss of $61.7 billion in the United States in 2019.
However, cameras fortified with video analytics are almost impossible to deceive. Algorithms fed to the system can easily detect shoplifting, internal theft, etc., and alert the security and law enforcement agencies in real-time to stop the theft. The risk of being caught is a powerful deterrent and can keep businesses safe.
Artificial Intelligence and Healthcare Industry The applications of AI are not limited to law and order but have also shown their usefulness in the healthcare sector. Governments all around the world have imposed multiple restrictions to contain the spread of Covid-19 but these are more often violated than complied with. With the reopening of public spaces and transport, there is a real risk of new hotspots emerging as businesses and people knowingly or unknowingly, violate the guidelines. Artificial Intelligence integrated into existing CCTV cameras to monitor the public places, can analyse the data in real-time to alert the public officials about the safety violations. Businesses not complying with the sanitary or crowd control guidelines can be easily recognized and warned. Video analytics can analyze if a particular place is being sanitized regularly, or whether staff and people are wearing masks as per the guidelines. This allows the security personnel to take action in a timely manner to avoid another hotspot.
Social distancing plays a vital role in containing the Covid-19 virus. A camera equipped with AI can identify if people are maintaining social distancing norms or not. Many companies are utilizing social-distancing detection tools with AI enabling technologies to ensure that the employees are adhering to the social distancing guidelines so as to prevent the occurrence of new hotspots.
Artificial Intelligence and the Retail Industry Video analytics provide useful analysis to retailers by recognizing the areas where the customers spend time and shop, through heat mapping. It can also help in recognizing the busiest hours of the day or the week and thus help in enhancing the customers’ shopping experience. It can also significantly help in reducing inventory loss as the data records can provide insights regarding the normal working hours, employees handling the inventory and other useful details.
Conclusion Summing up, it can be said that the world has just started to realise the potential of video analytics. Its applications can take monitoring to new heights. It can make the world a much safer place but with great power, comes great responsibility. If left unregulated, it can become unmanageable and hence, the ethical norms of monitoring need to be worked out by the governments around the world.
Our product, Wobot.ai, is an AI-powered video analytics application. It helps organizations across food services, retail, manufacturing and healthcare, to leave behind the challenges of manual video monitoring and adopt AI-driven monitoring.
Wobot has been adopted by top brands across the world. To check more about Wobot.ai and how it helped Cure.fit, one of India’s largest healthcare and fitness companies in handling its hygiene, safety, and day-to-day operations.
Source : https://wobot.ai/blog/using-ai-to-transform-the-video-monitoring-world-in-real-time/
AI-Powered Video Analytics for the Retail Industry
The retail industry is among the major users of artificial intelligence (AI) today. The industry has seen some major shifts in customer service, supply chain, waste management, inventory management, and demand projection through the use of AI, experiencing a boost in efficiency and profits. Although the journey of AI in retail has just begun, the promise of an exciting growth journey can already be seen through the gradual integration of AI-based analytics. One particular aspect of AI intervention in the retail environment is the utilization of video surveillance footage to optimize outcomes.
Human eyes can review just 1% of video surveillance footage
A fair amount of research has gone into the human potential of looking up all of the video footage of surveillance cameras. The research has revealed that humans have barely managed to glance through just 1% of all such video footage, and we are not even talking of a close review here. When you want to optimally utilize video footage in a retail environment, you need conclusive evidence of the operational gaps that need to be closed to improve output and performance. That can happen only when the footage is properly analyzed. This is where AI comes into the picture. With its ability to analyze such footage with acute precision and speed, AI can be a powerful tool in video surveillance for the retail industry.
Scale-up personalized customer service
An example of excellent AI execution in retail can be seen in the global coffee chain, Starbucks, which was struggling to send out just about 30 different types of email offers to its customers once in a few weeks. The offers were generic and lacked personalization. They began using AI analytics to personalize these promotions for their customers. The result was a massive increase in email engagement, resulting in an exponential growth in Starbuck’s sales. That’s the power of AI.
AI in the supply chain ensures faster growth
When businesses adopt AI to bolster their supply chains, the gains are substantial. A Mckinsey study found that over 53% of retail businesses experienced higher revenue growth and over 61% reported lower costs after using AI-based analytics.
Waste is not waste till it is wasted
The only way to generate a booming industry out of waste management is by adopting AI to scale up some exciting waste management processes, especially in the food retail industry. One retailer in Israel managed to reduce food waste by around 40% and saw revenues triple to almost 110% after it adopted AI to deal with an ever-growing waste management problem.
Precise demand analysis and projection
A vast network of cameras continuously studies every square inch of a supermarket. This kind of intensive coverage creates a massive load of video footage about customer and staff behavior inside the store. Analysis of such footage is bound to reveal informative data about customer preferences and staff performance for different products and brands. This is highly beneficial in optimum demand projections and procurement planning. Such invaluable data and analysis on a single platform can even lead to much better management of resources and level up customer engagement to a great extent. A study by Mckinsey Digital shows that AI-driven demand projections:
Can minimize errors by up to 50% in supply chains
Reduce warehousing costs by up to 40%
Bring down lost sales opportunities due to inventory stock-outs by around 65%
Improve average order fulfilment time by over 14%
Compliance is the key in labor-intensive enterprises like retail
Brick and mortar retail businesses are invariably labor-intensive and therefore, require different processes to sustain their operations along with compliance at different levels. A few areas where compliance plays a major role in the retail industry are:
Personnel Management: The most important aspect of any retail operation is overall staff compliance across different departments.
Inventory Management: Sustaining the size and variety of inventory in a retail store is possible only with proper compliance of the staff handling the inventory.
Customer Relations: Customer compliance is as important as staff compliance inside a retail store and needs to be handled carefully.
Waste Management: Minimizing or eliminating wastage of stock in the inventory is a major challenge and it depends on high rates of compliance.
The use of AI technology to achieve desired levels of compliance across different departments of a retail establishment is helping organizations to compete much better than they ever did before.
The analysis of video footage in AI can be scaled up to meet the needs of the largest operational units in retail establishments. This will work like a super-efficient force multiplier for such establishments as it will provide the minutes details about gaps in any process or workflow compliance. There is no other way to utilize the massive load of video footage from different corners of retail stores, their warehouses, and logistics chain. The use of AI-powered platforms to achieve higher levels of compliance and efficiency from its staff will help retail establishments to manage their economies of scale more optimally.
You can strategically improve your operations with the insights provided by Wobot’s Video Analytics and ensure a flawless customer experience.
Source: https://wobot.ai/blog/ai-powered-video-analytics-for-the-retail-industry/