Prakash PrabhuChief Business Officer & Co-Founder, VisionBot Computer vision has traditionally been used for inspection in highly structured manufacturing environments. But thanks to increasingly powerful machine learning techniques, and mature data labelling capabilities, Visual AI is becoming capable of monitoring more complex and dynamic processes where humans are involved, this is revolutionizing our approaches to identifying and mitigating failures in a wide range of industrial processes – expanding well beyond traditional automated manufacturing applications and promoting Human Centred AI (HCAI). The oil and gas sector, companies can adopt AI technologies to improve Operations, Safety and Reliability across the production and supply chain. This translates to autonomous processes, improving cost efficiencies, and reducing operational risks. Some of the process impacted by Visual AI include: Intelligent Fire Detection With AI Fire hazards are one of the most severe causes of accidents that may lead to casualties, considerable production loss, and equipment damage. Traditional fire detection was done by human operators through video cameras, especially in petroleum and chemical facilities. However, it’s almost impossible for human operators to spot fires in time with hundreds of video cameras installed in large-scale settings. Human subjectivity, distraction, and visual perception limit the accuracy of human safety supervisors. Intelligent fire detection applies computer vision methods to video cameras to detect fires. Some methods have shown better results when focusing on smoke detections. These use background subtraction to detect motion and reduce computational complexity. The availability of accurate model datasets and improved computation power of edge cameras can now make it possible to undertake complex analysis for Fire and Smoke detection on the camera. Predictive Maintenance and Equipment Failure Detection In oil fields and refineries, deep learning models can be used to detect equipment failures or deterioration. Therefore, custom neural networks are trained to detect anomalies during automated equipment inspection. If an AI model detects a potential issue, an image can be automatically sent to a human supervisor for manual review. By continuously monitoring equipment performance, they can predict potential failures, allowing for proactive maintenance to minimize downtime and prevent accidents. well where deep neural networks (DNN) are applied. Traditional methods of physical interpretation are time-consuming, and the results depend strongly on the human expert (subjectivity). In Industry tests, the ML model’s accuracy was 92% compared to manual interpretation and about 1,000 times faster than the manual method. AI methods can accelerate the process and, even more critically, exclude subjectivity in the interpretation process. Conclusion Today, we are only seeing the beginning of the era of Visual AI-driven applications. Edge AI makes it possible to move AI vision capabilities from the cloud to the field, enabling large-scale and distributed applications. Because of the strategic importance and distinct operational workflows, most oil and gas companies aim to build and operate their Visual AI solutions with a primarily aim to improve maintenance, safety, management, life-cycle sustainability, quality, and operational efficiency. As a leading Visual AI Company, VisionBot helps to leverage the latest in computer vision technology to help businesses and organizations automate processes, improve customer experiences, and gain valuable insights in to their operations. Connect with our experts to understand how companies are using VisionBot™ Visual AI driven Computer Vision to strengthen security, safety and streamline operations. We welcome Technology Integrators and sector speciality VAR’s to become a VisionBot™ channel partner, and discover the opportunity to offer a cutting-edge AI-powered computer vision solution to your customers. *Views expressed in the article are solely of the Author

Weaponized for Malicious Purposes GARIMA GOSWAMYChief Executive Officer and Co-FounderDridhg Security International Pvt. Ltd. On January 7, 2019, Gabon faced an attempted coup sparked by a suspicious video of President Ali Bango, coinciding with rumours of his failing health. Amidst the Russia-Ukraine conflict in February 2022, a deepfake video depicting Volodymyr Zelenskyy surrendering circulated, sowing confusion. Subsequently, in June 2023, hackers aired a fake televised emergency message supposedly from an AI-generated Russian President Vladimir Putin, declaring Martial law due to alleged Ukrainian incursions into Russia. There is also a viral interview of Russian President Vladimir Putin having a conversation with his deepfake, a student from St Petersburg State University. A snapshot of the same is given below: In India, a deepfake video of Bharatiya Janata Party’s Manoj Tiwari speaking multiple languages went viral on WhatsApp before the Delhi elections, resembling David Beckham’s multilingual ‘Malaria no more’ campaign. Initially surfacing in 2018, deepfake technology was exploited by a Reddit user to create objectionable pornographic content featuring celebrities, generating widespread skepticism due to a lack of awareness. More recently, financial frauds leveraging synthetic audio and deepfake videos, often combined with impersonation on video calls, have become prevalent. What began as a seemingly innocuous tool in the entertainment industry has spiraled into a technology facilitating misinformation, defamation, pornography, and financial fraud through social engineering tactics. Good DeepFakes Some uses of deepfake which is not necessarily unethical is the use of text-to-speech for writing audio books for the visually impaired and text-tospeech or speech-to-speech to create synthetic voices, that can be used in the entertainment industry. Then there is the concept of hyper-personalization. Recently, Cadbury used hyper-personalization as an initiative to make the famous Indian actor Shah Rukh Khan a brand ambassador for small businesses. Here videos were created by mixing a deepfake version of the actor along with some shots recorded for the campaign. Now companies like ‘True Fans’ are using hyper-personalization to send customized messages on special occasions at a cost. Understanding Deepfakes Deepfakes represent a form of manipulated media, combining ‘deep learning’ with ‘fake.’ Utilizing artificial intelligence and deep learning techniques, deepfakes involve altering or superimposing content onto existing images, videos, or audio recordings to create convincing yet entirely fabricated scenes. These manipulations often employ auto-encoder convolutional neural networks, which compress input images before reconstruction, or Generative Adversarial Networks (GANs), an unsupervised deep learning algorithm. GANs consist of a generator, which reproduces a specific person’s face, and a discriminator, which identifies flaws in the generated image, leading to iterative improvement until flaws are minimal. Where Lies the Solution? Just as proof of the pudding is in eating it, the detector is already present inside the deepfake creation. Also, some cues can help distinguish the real from the deepfake and some credible software that falls under the category of ‘deepfake detectors.’ It is important to sensitize people about the problem of deepfakes and present credible methods to distinguish the real and the deepfake. For image forensics and authentication of audio and videos, there are some reliable software available. A highly reliable image forensic software, particularly popular with law enforcement agencies in several countries is Amped Authenticate which uses multiple parameters for authentication of images. It conducts file analysis that is used to check the metadata of images. It can also be checked if an image comes from social media. A global analysis involves examining the processing history behind an image. The software through this analysis can demonstrate the presence of resaving, cropping, recapture, and editing. This helps to increase the accuracy of image analysis. Local analysis identifies possible manipulations based on the nature of JPEG file format and the traces left behind by editing software. Using color channels, error level analysis, JPEG ghost maps, and cloned artifacts identification, it is possible to demonstrate areas within an image which has possibly been edited. These are just some of its features. For detection of synthetic voices, a notable tools which comes highly recommended is ResembleAI’s detector. It is user-friendly and a wav or mp3 format file can easily be uploaded. It has two controls which have to be used – frame length and a sensitivity knob. Frame length controls for the granularity of the model’s analysis. By default, the model analyzes the file in 2-second chunks, then provides a real or fake prediction score for each chunk, and ultimately provides a weighted average score for the entire file. The smaller the chunks, the less likely that the chunk will contain both real and fake data, which ultimately improves the accuracy of the model. The sensitivity knob controls the level of scrutiny and aggression the model applies to its file analysis. The higher the sensitivity the more likely that the model will return a false positive result. Increases in sensitivity are meant to capture any instance of synthetic audio in an audio file, and flag the audio as fake. While there are several deepfake detectors which are available for checking the authenticity of videos such as DeepWare, DeepIdentify, Sensity, FakeBuster, FakeBuster by Intel, Kroop AI’s detector, Sensity is recommended as it has a high level of accuracy. It is to be noted that among these names, a distinctive feature of Fakebuster is that it can capture live videos and can be integrated with video conferencing platforms like Zoom and Skype. This made-in-India software is available as open-source and was developed in 2021 keeping in mind the risk of imposters in video conferencing particularly as the frequency of video calls increased after COVID-19. If such software was used, the 2024 Hong Kong fraud involving a finance executive who deposited $25 million to imposters after a fake Zoom call could have been prevented. We can’t only depend on deepfake detectors for this space is evolving regularly and there is a cat-and-mouse chase between deepfake creation software and deepfake detection software. And, no software can guarantee 100% accuracy. It is then important to rely on human intelligence too. Some warning signs and techniques that individuals can use…

In December 2023 organizations were still recovering from pandemic-related disruptions. Yet, despite labor shortages, supply chain issues, and growing cyber threats, leaders advanced their risk management plans. In 2024, the physical security industry will stay focused on growth. We believe that they’ll prioritize agility, data optimization, and resource efficiency in their decisions. Check out our top 8 physical security trends below: 1.IT and physical security teams will join forces Physical security’s convergence with IT is accelerating. And it isn’t limited to technology anymore. In the coming year, organizations will look to optimize collaboration between IT and physical security teams. sets will result in more effective risk mitigation and data optimization across the organization. And though there’s no one-size-fits-all approach, most will consider the following strategies: As this human-centered convergence grows, so will the demand for unified, cloud-connected physical security solutions. This will give teams a comprehensive view of systems and evolving risks while helping them extract more value from data. 2.The democratization of physical security data will surge The democratization of physical security data is well underway. More employees need to engage with physical security technologies and data than ever before. Our research shows that almost 40% of organizations are also struggling with physical security labor shortages. Gatekeeping access to specific tasks or information only compounds the strain on resources. As employee roles evolve in this digital era, organizations will seek more collaborative physical security technologies. They’ll want easy-to-use solutions that can support secure, limited-use applications for people outside of the security department. What could this look like? Crimescene witnesses securely sharing video from their phones to a centralized evidence repository or, team leaders overseeing access requests relevant to their department. For many organizations, this will lead to greater workforce augmentation across the enterprise. It will also help them expand the value of security investments to serve broader objectives. 3. Access control modernization will top tech investments Modernizing access control will remain a top priority in 2024. To ease upgrade complexities, many organizations will shift to a hybrid-cloud model and deploy cloud-ready access control solutions. This will deliver continuous innovation and cybersecurity updates that reinforce security from doors to networks. We’ll also see greater demand for open access control solutions. More than ever, organizations want the freedom to add and connect the best technologies out there. In 2024, this will include everything from building management systems and life and safety solutions to human resource management software and mobile credentials to name a few. Unifying access control with these various technologies can boost operational efficiencies and sustainability initiatives. They also allow employers to enhance the cardholder experience; one where everything feels more fluid and convenient. Many will also reach a breaking point in managing separate video and access control systems. Striving for more efficiencies, leaders will take steps towards system unification. This will simplify system monitoring and maintenance tasks, leading to higher output and costs savings across the enterprise. 4.Organizations will seek to maximize hybrid-cloud investment The physical security industry will see a large increase in hybrid-cloud adoption in 2024. Recent research found that 44% of organizations already have over a quarter of their physical security deployment in a cloud or hybrid-cloud environment. As cloud adoption rises, there’s a growing interest in new plug-andplay, cloud-ready appliances. They not only streamline access to cloud services but also enhance computing power at the edge. We’ll also see a larger focus on cloud data usage and associated costs. Those who are further along in their hybrid-cloud journey are seeking ways to optimize cloud spend. Many will lean on channel partners to explore use cases beyond security to maximize hybrid-cloud investments. 5.Cities will become focused on building public trust In recent years, police departments have been struggling to hire and keep officers. To offset this problem, many cities are investing in new crime-fighting technologies. Everything from vehicle investigation systems and situational awareness platforms to drones and body-wearable devices helps boost efficiencies across public safety departments. Yet as the use of technology expands across cities, so do public privacy concerns. In 2024, we’ll see a growing commitment from cities to build more public trust and strengthen privacy efforts. The following core strategies will be most helpful: 6.IIoT growth and data-optimized solutions will boom The number of physical security devices and other industrial internet of things (IIoT) sensors coming into the market is accelerating. And across industries, organizations can’t get enough. IT and security experts want to expand the types of data within their security deployment. Beyond that, they’re looking to extract data from the systems holding it and build data lakes that serve future objectives. At this critical moment, those who opt for an API-centric, open architecture, along with a unified physical security platform will stand to gain the most over time. This will give them the flexibility to combine and simultaneously analyze various sources of data on their own terms. Ultimately this can help inform new data-driven strategies and maximize returns across all tech investments. During this data influx, many organizations will also look for ways to empower their operators and digitize current workflows. As a result, demand for physical security solutions with embedded analytics, automation tools, and visual dashboards will grow. 7.Organizations will favor government-approved solutions According to IBM, the average cost of a data breach in 2023 was $4.45 million USD. And only one-third of companies were able to identify the breach through their own security teams. Moving into 2024, many organizations will use government directives and accredited certifications to guide technology decisions and scrutinize their supply chain. This will increase demand for government-approved, highly compliant physical security solutions. Today, the most stringent data protection requirements apply to government agencies and essential services. However, other organizations are paying close attention. By adopting similar strategies and solutions, they get access to the most advanced tools that help identify and contain threats faster. They can also prove trustworthiness by showing partners and customers they take cybersecurity seriously. The benefits are two-fold: stronger resilience and…

This blog explores the revolutionary impact of reinforced polyamides on anti-corrosion cameras. Discover how these innovative materials offer superior chemical resistance, durability, and strength, and how they stand out as a lightweight and cost-effective alternative to metal camera housings. We also explain why Hikvision’s Polymer Anti-Corrosion Cameras are the ideal solution for corrosion protection in the harshest environments Cameras installed in industrial or marine settings are constantly exposed to harsh chemicals, salt, or other corrosive materials. For these reasons, inner camera components that can be easily damaged in these kinds of environments need to be enclosed in strong, protective housings. Until recently, anti-corrosion cameras used housings made of metal, typically stainless steel or coated aluminum. While these materials can be very effective in terms of protecting sensitive camera components, they are also typically expensive and heavy, making them more difficult to handle and install. To overcome these challenges, the latest generation of anti-corrosion cameras use reinforced polyamides, which are light, highly durable and more cost effective than metal housing alternatives. Read on to find out why these cutting-edge materials are a game changer for anti-corrosion cameras in four key ways. 1.Resilience against various kinds of chemicals and corrosive materials In the process of corrosion, oxygen, acids, salt and other substances convert metals into more chemically stable oxides. This can damage them and prevent them from fulfilling their intended function, requiring metal components to be treated or coated with special chemicals. Reinforced polyamides require no such protection as they are almost immune to corrosion. The secret behind this is the strong chemical bonds that hold polyamides together, as well as the extra reinforcement provided by the blended materials. The tight molecular structure of the polyamides provides greater stability and durability, leaving very little chemical energy available to react with other substances, even the most aggressive oxidants. According to the British Plastics Federation, polyamides provide good resistance to most chemicals. Hikvision’s rigorous acid, alkali, and salt spray tests have proved that a polyamide, when reinforced, can exhibit exceptional material integrity. 2.Protection against abrasion, impacts, and the passage of time Naturally present in wool and silk, polyamides are more often seen in synthetic products. Sports gear and dental floss demonstrate the reliability and strength of these materials, which are also used frequently to replace metal components in all kinds of machinery and equipment. In a Hikvision laboratory test, a specific reinforced polyamide demonstrated 90% of the strength of aluminum. Notably, it was able to withstand repeated high-energy impacts with no signs of fracture, demonstrating its suitability for high-demand security scenarios and devices. Reinforced polyamides are also strong enough to resist the ravages of time. Subjected to rigorous 1,000-hour xenon aging tests in the Hikvision lab, the tested reinforced polyamide maintained its appearance and resilience in a way that regular plastics are unable to. 3. Reduced camera weight and less hassle for installers Heavy stainless-steel-cladded cameras, which typically weigh up to 25kg, are difficult for installers to handle safely. In many cases, it is simply impossible for a single person to do the installation. The same volume of reinforced polyamides are significantly lighter than their metal counterparts. A reinforced polyamide typically has a density less than half that of aluminum and only a seventh of stainless steel. This weight differential changes the game for installers, making anti-corrosion cameras much less cumbersome and much easier to install and maintain. 4. New levels of cost effectiveness Reinforced polyamides are typically far more cost effective than metals. Their lighter weight also provides significant savings in terms of transportation, warehousing, and installation costs. The superior durability of reinforced polyamides in harsh environments also reduces the need for repairs and maintenance, delivering major savings for larger installations on public roadways, in industrial parks, or in similar settings. Security cameras with reinforced polyamide housings offer excellent performance and durability at a highly competitive price-point. This makes them an excellent investment for users and helps to maximize RoI over the product lifecycle. Introducing Hikvision’s reinforced polyamide anti-corrosion cameras Hikvision’s newly released Polymer Anti-Corrosion Cameras feature state-of-the-art reinforced polyamide housings and accessories. They increase durability and cost effectiveness for our customers, as well as reducing the weight of each camera unit. Additionally, the cameras are equipped with Hikvision ColorVu and DarkFighter technologies for excellent color imaging, even in ultra-low light. A range of built-in deep learning analytics capabilities help end users to maximize security and reduce false positives. Additionally, third-party or custom applications can be integrated easily into the cameras, making them ideal for even the most complex security needs. The new Hikvision anti-corrosion cameras, which are wrapped in tried-and-tested reinforced polyamide, offer a durable, lightweight, cost-effective security solution, even in the harshest industrial and marine environments.