AI Driven Automated Visual Inspection & Content Analysis
Prakash Prabhu – Chief Business Officer & Co-Founder, VisionBot In the past few articles, we have discussed about Computer Vision and how it can address the challenges faced by many diverse processes across multiple Industries. With the staggering amount of video content generated by billions of video sensors across the globe, the capabilities of CCTV video surveillance systems are now being transformed by fundamental shifts in how video data is gathered, stored, accessed, and analysed. VIDEO Cloud is enabling a massive transformation in the ease of monitoring and analysis for data driven Digital Enterprises Visionbot™ – Enabling the Convergence of the VIDEO Cloud and AI/ ML for Computer Vision applications VisionBot was incorporated, with a focus to address the demand for VIDEO driven digital enterprise. VisionBot AI enabled Computer Vision, helps augment performance of workflow processes and enables improvement of overall Operational efficiency of an Enterprise. It cost-effectively manages distributed visual sensors at scale, analyses the massive volumes of visual data with artificial intelligence and distributes personalized, actionable information to decision makers. The AI enabled VisionBot VIDEO cloud computer vision platform was built for accessibility, affordability and availability. Bringing the benefit of cognitive Video AI for ALL is the most important part of our journey to address the Video driven roadmap for any organization. Generative AI will probably be the singularly adopted tool for generating adaptive video content to boost engagement and drive collaboration across enterprises and social engagement. What excites us is the reality of VIDEO becoming the primary driver of the creator economy. It is inevitable that video will remain an important tool whether for work, entertainment, and learning. VisionBot will be synonymous for all things related to the AI driven VIDEO cloud. This journey of VIDEO based transformation, has opened a lot of conversations around the technology, its challenges, and the benefits for the early adopters of the AI driven VIDEO cloud. What are the industry problems that are being addressed? Among all the workflow processes within any enterprise today – visual inspection and monitoring is still heavily dependent on human reporting. Human assessment and reporting are however subjective and is prone to errors due to fatigue and inconsistency/ non repeatability. It also slows down the overall process throughput which are otherwise completely automated. VisionBot AI driven computer vision helps companies to reduce operational costs and mitigate safety and operational gaps through custom object and event detection. Automates visual monitoring. Workflow automation and reporting. Improved accuracy of actionable object data. Our Generative AI models will be assistive for attainable goals to drive long-term video adoption. Recruiting early adopters, setting content strategy, and making sure enterprises have the right technology to support goals for a more effective use of video. Increase employee-created content. Drive content diversity. Choose the right generative AI Tools. Ready to scale. A. How does this compare with traditional technique/s? 1.Traditional Rule-based automation systems are rigid Traditional rule based video content analysis has been incorporated in cameras (Edge) and server-based analytics server on the premise. Rule-based automation is a system that applies manmade rules to store, sort, and manipulate data. To work, rulebased systems need a set of facts or sources of data and a set of rules for manipulating. We sometimes refer this rule to as an ‘If-else statement’ because it must follow instructions. 2. Rule-based automation need humans to identify all scenarios in advance If you want to create a rule-based system capable of handling 100 different actions, we must write 100 different ‘if-else’ rules. Any need to update the system and add more event alerts, then we need to write a new rule. The system does not work on its own or make intelligent decisions. Rules-based systems will also not change or update, and will not ‘learn’ from mistakes, so accuracy levels do not improve. 3. Cognitive analysis based intelligent automation can accommodate wide scopes In comparison with rule based systems, VisionBot AI driven computer vision which is intelligent automation that with the help of artificial intelligence, helps to automate more activities. Artificial Intelligence includes three broad areas of computer-vision/ image-recognition, (NLP) natural-language processing and (ML) machine learning (to predict outcomes). With a combination of these capabilities, we can build automation that is more human-like with model training. Companies today face several challenges: increasing efficiency, improving decision-making, staying competitive, ensuring customer loyalty and compliance are just some of many obstacles that businesses face, cognitive automation is effective in overcoming these key challenges by supporting companies in optimizing their day-to-day activities and their entire business. The benefits that result from cognitive automation also include improved compliance and overall business quality, greater operational scalability, reduced turnover, and lower error rates. All of this has a positive impact on business flexibility and employee efficiency. Based on our experience, we believe that a company can expect savings of over 50% on its production activities and a reduction in the relevant costs. B. This is relevant for large corporates, not for MSMEs? While large-scale enterprises have long begun using new technologies like machine learning and artificial intelligence (AI) to streamline their business processes, SMEs (Small and Medium Enterprises) are still lagging behind in their effort to embrace the digital data driven enterprise. Primary Reasons for slow adoption: How VisionBot mitigates this for MSME High cost of deployment: CAPEX: VisionBot subscription model allows all companies to adopt Video based AI in to their organization processes at near zero costs. On the contrary, their existing investment in Video surveillance devices are used more effectively for organizational effectiveness apart from pure surveillance and safety. Fast changing technology landscape: VisionBot AI driven video cloud which is hosted on AWS/ AZURE, ensures companies get the best of computing hardware, data security and scalability without the need to hire a technical expert for cloud or AI technologies. Fear of getting locked in: VisionBot AI driven video cloud is ready with a wide model set of object detection behaviours and user configured event alerts. Users can flexibly select and change between different…