Tag: Computer Vision

Be aware of the practical side of AI implementations

Posted on by SuperAdmin

Overcoming the Hype

Accessibility of useful data, heavier computing power and advanced algorithms have in recent years resulted in companies looking at AI to help drive efficiency, cut costs, increase revenues, automate routine tasks, improve employee experiences and understand their customers better. More and more use cases were also being conceptualized for strategy and innovation by a large number of corporates globally.

Major investments were made in the past across multiple industries to try and utilize data and AI strategically. However, several companies who initially scrambled to implement AI in their organizations did not eventually get to enjoy the benefits they had envisaged at the start. This lead to fears, somewhat justifiably, that AI is over-hyped. Of course it was over-hyped then.

AI-Ups and Downs

AI went though many ups and downs. It took several case studies and analysis of companies, people and systems deployed in AI projects to understand that the problem in most implementations was a basic lack of understanding of what AI is capable of, how to practically leverage data, and what the dangers are that need to be side-stepped to ensure real value for the business.

The fact that AI was hyped and why it was so has now created an appreciation of the need to implement it properly, but also a fresh awareness of its huge potential and how it can be a real value driver if done properly. Businesses today widely accept the fact that they must adopt AI strategies in order to compete. But they also need to beware of the pitfalls in going ahead without a clear cut plan or process.

How you Approach AI is the key

AI has proven its value across various sectors in multiple industries. While more and more use cases are being addressed by AI, an Accenture survey in 2021 revealed that most organizations are barely scratching the surface.

Even before the pandemic hit it was evident that many businesses were achieving significant RoI by rolling out AI beyond the pilot stage. During the last couple of years AI transformation became the very means of survival for many, whereas for others it became a catalyst for growth.

But what was the secret to these superior performances that have set new standards in AI implementation?

What set them apart is how these companies approached AI. They did not just adopt the Cloud and start using AI and data solutions. It is more about how they put a lot of thought into it, analysed the organization and the business environment and the pitfalls, and strategized before they actually tapped into any of the widely available AI technologies. The successful AI achievers were those that put people and systems first(digital transformation strategy), and technology later, and who looked at AI as a differentiator to stay ahead of the game.

The Strategy

First, do a holistic research and determine what AI can and cannot do for you. What exactly do you want to achieve? Is it to solve a problem, or to tap an opportunity, or get new insights, or is it for a total reinvention of your business? How and where to start, and what are the difficulties? Pick the brain of a data scientist if you can associate with one.

Draw up a list of potential use cases and a roadmap including a long term vision. Priority could be the low hanging fruits, the easy wins. Most importantly, understand what type of data is available and where, and what are the additional types of information that needs to be tracked to implement the chosen use cases.

The Team

You may not have all the required skills in-house to implement AI. Building a team or finding an AI partner with the desired capabilities is another important step. In fact, building the right team with the same mindset and personal skills to work with the rest of the organization can be the most critical factor in the long run. Businesses need to understand that this is not an isolated project but an integration of a new and soon-to-be-scaled AI platform into an existing IT eco-system.

The quick MVP and Roll-out

Develop the solution to your first business problem quickly, ideally within 2 to 3 months. This MVP (Minimum Viable Product) should have enough functionality, value and benefit for the user to sustain its usage and also a feedback loop to enable further development. Engage an expert who is savvy both technically and in the business sense. Sit with him and define the key performance parameters over the initial roadmap period. Review these regularly and modify them if necessary down the line.

After the MVP has demonstrated its value and been evaluated, prepare to rollout on a broader scale. Utilize your AI partner’s expertise and experience to keep in perspective both the technical and business factors during the implementation stage.

Addressing some typical problems

Organizations heading for AI implementations must give due consideration to these important issues they will face for sure.

Reluctance to change – This is an age-old management problem, but for AI implementation it refers to changing your decision making process into a data-driven one and not just based on instincts. To overcome this, some visible and measurable benefits have to be revealed early. That is where a quick MVP in a particularly relevant use case will help.

Lack of involvement – The users need to feel they are part of the solution and not being forced to adopt something that is being imposed on them. The environment has to be such that they are well taught and feel themselves to be joint architects of the project. Set realistic expectation levels and a roadmap for achieving results. Support of key management personnel and stakeholders are also critical for creating the right environment.

Quality and availability of data –No doubt that clean data is a key factor. So, centralized monitoring and control to obtain incoming data in a standardized format is absolutely necessary. There is also the challenge to locate and keep track of the right data and how and where it is stored. Do not go for complex machine learning models and stick to simpler solutions, if you do not have enough good data or sufficient labeled data that can be used to train the system.

Skillsets and Infra for implementing AI – It may be less challenging and cheaper to outsource than form a huge in-house team. In any case you need to do an evaluation study of what’s available internally and also define the costs going forward, keeping scalability also in mind.

About Cogniphi

Cogniphi is a technology company that enables customers to achieve transformational outcomes through cognitive digital solutions.  Cogniphi’s Vision Intelligence platform AI Vision integrates Computer Vision, Machine Learning, and AI to extract precise and meaningful data from visual footage. These are further converted into actionable insights and notifications.

References

https://www.mckinsey.com/capabilities/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021

https://www.gartner.com/en/articles/cfos-here-are-4-actions-to-ensure-you-implement-ai-the-right-way

Your surveillance system might be the chink in your armour. Make it fool-proof with AI Vision

Posted on by SuperAdmin

Dozens of digital eyes peer at us today – guarding us from the moment we step out of our homes, and sometimes even before. We have surveillance cameras watching over our gates, our roads, and our offices, and even overseeing us in shops, malls, and ATMs.

Between Chennai, Hyderabad, and Delhi being among the top ten cities in the world with the highest number of CCTV cameras per square kilometre, and video surveillance buttressing Indian investigative agencies as they crack violent cases – these cameras have already proven themselves to be indispensable. It is, therefore, imperative to have cameras surveying your company’s premises, and to use them as the bedrock of your business’ security structure.

But these digital eyes are only as good as their human counterparts monitoring a feed. CCTVs’ watchful presence might prove to be a powerful deterrent, but their passivity results in complete reliance on external forces for intervention. These days, law enforcement too depends on captured footage to solve crime.

Things are changing, however, with  AI Vision (Artificially Intelligent Vision) – the tool that effectively marries computer vision algorithms with data-driven learning of Artificial Intelligence. Installing vision intelligence technology amplifies a company’s video surveillance system, transforming billions of hours of footage from an overwhelming wave of monotony into an organized database to apprehend perpetrators.

Here are six ways in which computer vision can help your company reduce security risks:

Identification

Cameras with AI Vision are significantly more adept at recognising and labelling objects – whether human, vehicle, or weapon. Installing this technology is an easy investment, especially considering most facilities are equipped with CCTV cameras.

This intelligence elevates an average camera, making it accurately identify a human presence even in the case of a partial capture. This process can even be widened to study people’s proportions and gaits, and can be trained to identify people based on these traits – even during less than ideal circumstances.

Automated identity recognition

The specificity that computer vision-powered cameras allow for, based in the technology’s pattern-recognition techniques, enables them to verify the identity of individuals based on extremely distinct features – like biometric identification through iris and retina scans. By extension, this technology allows for digitising all company documents since signatories can be corroborated through this highly precise process. These modes of biometric authorisation simplify and solidify security processes, and consequently reduce the scope for fraudulent activities.

Future forward

With the possibility of analysing movements and recognizing suspicious behavior in real time, and immediately notify authorities. Something as minute as a deceitful glance can be captured. From ringing alarms exactly when an item is shoplifted, to alerting authorities, vision intelligence turns CCTV cameras into a proactive part of cracking crime. Computer vision can also identify contextually dangerous behavior – such as a worker showing signs of fatigue and dozing off while operating high-risk equipment.

Outside of security concerns, these AI Vision capabilities can track behavior to provide detailed insights into what stakeholders and business partners respond to positively and negatively on company premises. Just tap into the data AI Vision gathers on your organisation’s performance indicators – from customer satisfaction to client retention rates.

Omnipresence: Computer vision can monitor all visitors on the premises, and alert security teams in a fraction of a second if an attempted robbery or security breach is occurring. The response – such as locking down the area – can be immediate. This promptness, along with hyper-specific discernment, enables security teams to share access privileges on an individual level, and allows them to even track miscreants through vision intelligence.

Furthermore, critical assets can be surveilled in real time – whether they are highly valued technologies or cash. Cogniphi’s AI Vision collection of historical data and pattern-learning capabilities can even offer a guide to where human resources need to be focused to strengthen the company’s security structure. And in case the crime has already occurred, security personnel can rely on the database to sift out relevant information within seconds – whether that detail is a man in a blue shirt, or a license plate. Computer vision – through a technique called “generative adversarial networks” – even offers the ability to enhance and recreate images, providing security teams more valuable visual details around critical incidents.

Safety measures: The midst of a raging pandemic, Vision Intelligence-enabled cameras can ensure that employees and workers socially distance on the premises. This technology can also alert workers who are dangerously close to hazardous equipment, or toxic substances.

Computer vision’s deep learning faculties can also understand manufacturing and standard operating procedures, and make sure materials and processes are being handled safely on the factory floor.

Similarly, Cogniphi AI Vision can track statutory compliance and make sure the company adheres to rules and regulations including the Factories Act, Shops and Establishment Act, and even Sexual Harassment of Women at Workplace (Prevention, Prohibition, and Redressal) Act.

Quick training: Newly hired employees can receive access privileges based on their scope of work. AI Vision’s expanding database can also serve as an exhaustive resource when it comes to training workers on standard operating procedures, and areas that need the focus of increased human resources – for instance, deploying more security personnel at risk-points.

Computer vision capabilities don’t replace human resources, rather they enhance and augment manned security systems. AI Vision’s surveillance offerings can predict critical security instances before they occur, prevent them from happening through a real time warning system, and protect you and your company’s valuable assets. This is an irrefutably reliable way to make your security systems proactive and fortified.

What Is AI Vision and Why Is It Here to Stay?

Posted on by SuperAdmin

Artificial Intelligence is one of the most misunderstood and overused buzzwords of our generation. We hear so many organizations bragging about their use of AI without really understanding what they are doing with it. In this blog post, our experts share how Artificial Intelligence is used in Cameras to improve business operations. Also, learn why it will become the future of how we do business.

Computer Vision is the application of Artificial Intelligence (“AI”) through a visual medium, like a live camera feed or an image. It essentially aims to replicate human perception and visual cognition. You must have already encountered computer vision without even realizing it, for example, the face-lock on your phone screen, to some level, is a simple application of computer vision or the Instagram or Snapchat filters that alter your hairstyle or turn your face into an animal on the screen, are all made possible with Computer Vision.

Any device that can comprehend a visual feed like a human being is a computer vision system, however, Computers have the ability to process more than humans can. Think about yourself reading these words. It’s likely that you’re focusing on one word at a time while you are reading, and recognizing the words around these words without fully processing them. Using Computer Vision, a computer would be able to see and read all the words on the page at the same time, drawing immediate meaning from the entire page

This principle also applies in a CCTV control room. Normally you would have people monitoring the live camera feeds on multiple screens, but how many live feeds can one person accurately monitor at a time? That’s where Computer Vision shines. It’s able to continuously and accurately monitor the feeds from all cameras simultaneously.

Automation integrated with AI Vision enables the workforce to overcome typical challenges of humans, like fatigue. It provides unseen insights that humans find difficult to access or comprehend in real-time. While human perception has its own share of limitations, a camera can gather every second of visual data from your premises that can be further analyzed to identify areas typically missed by humans.

Computer vision is the most natural next step in machine evolution. The purpose of AI is not to replace humans but to assist them. For that to happen, it needs to command similar cognitive abilities with enhanced capabilities. However, the underlying science behind AI Vision is not as complex or overwhelming as it might appear. Here’s a brief understanding of how AI Vision functions:

Capture Metadata from Camera Feeds

Content feed from a camera is analyzed by trained models to recognize objects, their actions, specific characteristics, and interactions in space and time. Typically, in a retail store, a camera equipped with Cogniphi’s AI Vision can detect shoppers, analyze footfall, recognize customers with face recognition, and evaluate customer expressions like anger with emotion recognition. Similarly in manufacturing, AI Vision can do myriad tasks such as identifying quality for inspection, counting warehouse inventory, etc.

Pattern Recognition and Anomaly Detection

Computer Vision derives relevant insights from unstructured data through contexts and occurrences of patterns along with their co-relations. In a retail store, AI Vision can analyze shopper dwell time, shopper interaction with products, alert anomalies such as misplaced objects in the wrong area, water spillage, and identifying reasons for inventory shrinkage, etc.

Recommendations and Predictive Analytics

Smart Vision equipped with actionable insights provides recommendations in the form of real-time alerts, analytics, and also integrates with existing business systems.

Cogniphi’s AI Vision is a pioneer in providing hyper-local computer vision solutions to retailers and manufacturers. Different components of the solution cater to different aspects of visual data and analytics to

– detect objects and their interaction in space and time.

– detect human body parts, their movement, interactions with real-world objects, their transformations, and other associated patterns.

– detect human faces and recognize people in 1:1 (Verification) and 1:N (Identification) mode.

– detect attention, emotions, and expressions on the faces

– identify and detect textures of objects.

– extract data from several documents and categorize data to train the model to interpret and analyze this data.

AI Vision is Here to Stay

Vision Intelligence technology is a cost-effective upgrade to existing data feeding cameras. On top of being a non-disruptive installation, Cogniphi’s AI Vision can help an enterprise reduce human error and experience overall increased productivity.

The Grand View Research states the growing valuation of the global computer vision market is expected to go up from $11 billion in 2020 to reach $19 billion by 2027. Manufacturing, Energy, Retail, Transportation, and Healthcare are the industries identified as best positioned to capitalize on this technology in the coming years.

The 2020 McKinsey Global Survey on AI has concluded that 50% of companies have adopted AI in one or other business functions and that the majority of use cases are aimed at optimizing operations or at product development or at customer service improvement. As companies increasingly look at AI to solve real-world challenges that depend a great deal on visual inputs, computer vision will have a huge role to play in achieving these objectives.

About Cogniphi

Cogniphi is a technology company that enables customers to achieve transformational outcomes through cognitive digital solutions. It believes in a 360-degree problem-solving approach, building solutions that can scale and adapt to changing business demands for continuous improvement.

Your surveillance system might be the chink in your armour. Make it fool-proof with AIVI

Posted on by SuperAdmin

Dozens of digital eyes peer at us today – guarding us from the moment we step out of our homes, and sometimes even before. We have surveillance cameras watching over our gates, our roads, and our offices, and even overseeing us in shops, malls, and ATMs.

Between Chennai, Hyderabad, and Delhi being among the top ten cities in the world with the highest number of CCTV cameras per square kilometre, and video surveillance buttressing Indian investigative agencies as they crack violent cases – these cameras have already proven themselves to be indispensable. It is, therefore, imperative to have cameras surveying your company’s premises, and to use them as the bedrock of your business’ security structure.

But these digital eyes are only as good as their human counterparts monitoring a feed. CCTVs’ watchful presence might prove to be a powerful deterrent, but their passivity results in complete reliance on external forces for intervention. These days, law enforcement too depends on captured footage to solve crime.

Things are changing, however, with AIVI (Artificial Intelligence Vision) – the tool that effectively marries computer vision algorithms with data-driven learning of Artificial Intelligence. Installing AIVI technology amplifies a company’s video surveillance system, transforming billions of hours of footage from an overwhelming wave of monotony into an organized database to apprehend perpetrators.

Here are six ways in which computer vision can help your company reduce security risks:

Identification

Cameras with AIVI are significantly more adept at recognising and labelling objects – whether human, vehicle, or weapon. Installing this technology is an easy investment, especially considering most facilities are equipped with CCTV cameras.

This intelligence elevates an average camera, making it accurately identify a human presence even in the case of a partial capture. This process can even be widened to study people’s proportions and gaits, and can be trained to identify people based on these traits – even during less than ideal circumstances.

Facial recognition

The specificity that computer vision-powered cameras allow for, based in the technology’s pattern-recognition techniques, enables them to verify the identity of individuals based on extremely distinct features – like biometric identification through iris and retina scans. By extension, this technology allows for digitising all company documents since signatories can be corroborated through this highly precise process. These modes of biometric authorisation simplify and solidify security processes, and consequently reduce the scope for fraudulent activities.

Future forward

With the possibility of analysing movements and recognizing suspicious behavior in real time, and immediately notify authorities. Something as minute as a deceitful glance can be captured. From ringing alarms exactly when an item is shoplifted, to alerting authorities, vision intelligence turns CCTV cameras into a proactive part of cracking crime. Computer vision can also identify contextually dangerous behavior – such as a worker showing signs of fatigue and dozing off while operating high-risk equipment.

Outside of security concerns, these AIVI capabilities can track behavior to provide detailed insights into what stakeholders and business partners respond to positively and negatively on company premises. Just tap into the data AIVI gathers on your organisation’s performance indicators – from customer satisfaction to client retention rates.

Omnipresence: Computer vision can monitor all visitors on the premises, and alert security teams in a fraction of a second if an attempted robbery or security breach is occurring. The response – such as locking down the area – can be immediate. This promptness, along with hyper-specific discernment, enables security teams to share access privileges on an individual level, and allows them to even track miscreants through vision intelligence.

Furthermore, critical assets can be surveilled in real time – whether they are highly valued technologies or cash. AIVI’s collection of historical data and pattern-learning capabilities can even offer a guide to where human resources need to be focused to strengthen the company’s security structure. And in case the crime has already occurred, security personnel can rely on the database to sift out relevant information within seconds – whether that detail is a man in a blue shirt, or a license plate. Computer vision – through a technique called “generative adversarial networks” – even offers the ability to enhance and recreate images, providing security teams more valuable visual details around critical incidents.

Safety measures: The midst of a raging pandemic, AIVI-enabled cameras can ensure that employees and workers socially distance on the premises. This technology can also alert workers who are dangerously close to hazardous equipment, or toxic substances.

Computer vision’s deep learning faculties can also understand manufacturing and standard operating procedures, and make sure materials and processes are being handled safely on the factory floor.

Similarly, AIVI can track statutory compliance and make sure the company adheres to rules and regulations including the Factories Act, Shops and Establishment Act, and even Sexual Harassment of Women at Workplace (Prevention, Prohibition, and Redressal) Act.

Quick training: Newly hired employees can receive access privileges based on their scope of work. AIVI’s expanding database can also serve as an exhaustive resource when it comes to training workers on standard operating procedures, and areas that need the focus of increased human resources – for instance, deploying more security personnel at risk-points.

Computer vision capabilities don’t replace human resources, rather they enhance and augment manned security systems. AIVI’s surveillance offerings can predict critical security instances before they occur, prevent them from happening through a real time warning system, and protect you and your company’s valuable assets. This is an irrefutably reliable way to make your security systems proactive and fortified.

Roadmap for Vision Intelligence and why more industries will embrace Vision AI

Posted on by SuperAdmin

Over the past ten years, Artificial Intelligence or AI technology has hurtled towards unimaginable advancements. And even though most people remain unaware of what AI tech such as Computer Vision (CV) or Vision Intelligence entail, chances are that they’ve already used it. AI has ubiquitously entered all our lives; it is helping us to drive smarter, unlock our phones faster, shop better, and soon, it will be a part of almost every aspect of our lives.

What is CV or Vision Intelligence and why will we see more of it in the years to come?

As human beings, we have the amazing ability to sense our surroundings. With the help of our eyesight and cognitive capabilities we can visualize what is around us and make decisions based on what we see. Computers on the other hand, aren’t able to do this automatically. CV or Vision Intelligence is thus a subset of AI that enables computers to see, identify, and interpret visual data as humans would. The process is complex and requires vision algorithms and applications for the computer to learn. However, once the process is complete, computers can see, interpret, and analyse visual data much better and faster than any human ever could. In addition to being more efficient, Vision Intelligence is also an extremely malleable technology. From automobiles to agriculture, Vision AI can be tailored to meet the requirements of all sorts of industries and its uses are wide-ranging. Below are examples of how Vision AI is being customised to help a whole host of industries.

Manufacturing

Vision Intelligence has been a revolutionizing force in the manufacturing space. From smart factory floors to quality control and accident prevention, Vision AI can help with almost every manufacturing process. In a modern factory setup, automated production lines are fitted with multiple moving machines such as conveyor belts and robotics units. For seamless production to continue, none of these systems can afford a breakdown. However, more often than not, stoppages do happen and they hamper production. Here is where Vision AI steps in. Armed with AI-based vision, CCTV cameras can analyse and diagnose every minor defect in a production line and issue real-time updates in case of machine failure or other problems. For example, if a conveyor belt is stuck due to improper material alignment, CV will preemptively flag the issue and notify the shift manager. Or, if a worker is standing too close to a vat of dangerous chemicals, AI-based CV systems can issue a red alert, thereby avoiding an accident. These are just a few examples of how AI has been a game-changer in manufacturing.

Retail

Retail is another sphere in which Vision Intelligence is creating ripples. For too long now, retail stores and supermarkets have faced a host of issues such as inventory mismanagement, revenue loss, and theft. Vision Intelligence has a solution for all of this. With the help of CCTV systems, and cameras placed on shelves and other crucial points, images of products and customers are captured, processed, and analysed to help retailers draw actionable insights. Vision-based tech and Deep Learning algorithms thus help generate insights like the effect of product placement on sales and customer shopping patterns in order to create more effective and personalised shopping experiences. AI Vision-powered cameras can also help to detect theft or incidents of sweethearting which is a form of theft where cashiers or checkout counter employees can give away merchandise to a “sweetheart” customer such as a family member or friend.

Health

In healthcare, Vision AI has the potential to save lives. Technologies like Automated Pathogen Detection combine the power of AI and automation to help test samples of human tissue, sputum etc. in a faster and more accurate manner. Meanwhile, there are several other AI-based tools that are being developed to analyse three-dimensional radiological images – a process that could potentially speed up diagnoses and suggest much-more effective treatments for patients.

The above three industries are just a few of the examples out of a vast pool of sectors that Vision Intelligence is making a splash in. In the years to come, Vision Intelligence or Computer Vision will grow in its reach and capabilities, and more and more industries will realise its multifaceted potential.