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

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

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.

Automated Pathogen Detection is set to transform pathology and here is what you should know about it

52-year-old Rakesh Singh walks into a primary health care center in rural Rajasthan with what seems to be a suspected case of Tuberculosis. After hours of waiting in line, his sputum sample is collected and sent to a lab for a sputum smear microscopy. Days go by but Rakesh’s results turn out to be inconclusive, and his diagnosis and line of treatment are subsequently incorrect. Although Rakesh’s case is fictional, the reality of TB in India isn’t. According to the WHO, India recorded about 2.69 million cases of TB in 2018 and the country’s caseload is the highest in the world.

What if there was a way to make TB diagnosis better, faster and error-free? What if there was a way to fine tune the process of sputum smear microscopies? Here is where Artificial Intelligence (AI) and Automated Pathogen Detection hold some answers.

Automated pathogen detection might sound like futuristic words out of a medical lexicon, but thanks to advances in AI, it is fast becoming a reality in laboratories across the world. In essence, Automated Pathogen Detection is a process that combines the power of AI and automation to help test samples of human tissue, sputum etc. in a faster and more accurate manner by eliminating the need for manual human labour. Take for example the process of a Sputum Smear Microscopy (SSM), which is still the primary method for diagnosis of pulmonary tuberculosis in developing countries like India. For an SSM, sputum collected from a patient’s lung is placed on a slide and stained to highlight the bacteria which are then counted by hand. The process of counting thousands of tiny strains is extremely tedious, manual, and time-consuming.

Automated pathogen detection that is aided by advanced artificial intelligence offers a revolutionary solution to this. Vision-enabled AI software can help analyze microscope output that is fed from digital cameras as video. The video is then converted into a series of images and the bacterial load is identified and counted from these images. Aided by AI neural networks and a workflow that is augmented by vision intelligence, the possibility of human error is completely weeded out and samples can be tested 24×7 at a much faster rate. Tuberculosis is just one of the myriad examples; AI-augmented workflow is now also beginning to play a pivotal role in cancer diagnoses wherein tissue biopsy samples can be analyzed more pertinently and effectively, leading to potentially life-saving diagnosis. And in the years to come, AI-aided workflow will find more applications in diagnostic pathology.

One of the main reasons why technologies like Automated Pathogen Detection are finding a stronger foothold in medicine is because they help tackle the decades-long challenges posed by traditional pathology. Medical professionals have been sounding the alarm about scarcity of pathologists and the issues with physical storage of slides in diagnostic pathology for many years now. India, for example, has a load of nearly 40 million sputum samples that are collected annually, and the volume is only set to increase year-on-year. Proliferation of AI-based technology could mean that images of slides don’t need to be physically stored and instead, they can then be digitally archived and even printed in a report. AI-augmented workflow is also largely operator-independent and requires very little human intervention. This could mean that low and middle income countries like India that have a shortage of skilled pathologists need not lose out on high quality and accurate diagnosis. AI-augmented workflow that is empowered by vision intelligence has the potential to address these and a host of other challenges in medicine.

Apart from being a game changer in diagnostic medicine, Automated Pathogen Detection is also the perfect embodiment of the promises that new-age tech, AI, and automation hold. In an article developed by the World Economic Forum, it was envisioned that in the Fifth Industrial Revolution, humans and machines will dance together! This of course is metaphorical, but it perfectly encapsulates the essence of technology such as Automated Pathogen Detection that is not meant to replace pathologists but instead support them and help them make rapid and accurate decisions that can save lives.