Hello all, so let me introduce myself. so I have overall 15 years of IT industry experience with a robust background across financial technology, digital marketing and automobile sectors. I excel in platform engineering, reliability engineering and DevSecOps SaaS operations and service delivery. My expertise includes multi, Tenant SaaS applications and cloud native microservices and streaming data platforms complex event processing, event stream processing and cyber security Like today we are stepping into the future of fleet management, where transformative technologies are reshaping, the way manage and operation operate vehicle fleets with the integration of artificial intelligence and the internet of things and Kubernetes. We unlock new possibility of efficiency and safety fleet management is the process of managing. let me introduce about What is fleet management? Fleet management is the process of managing a company's vehicles and assets through their life cycle. The goal is to improve efficiency and reduce cost and increase performance. The fleet care, fleet management itself like Itself introduced is a process of improving the efficiency and cost and performance. how about integrating AI, like AI and, IOT along with this fleet management and along with the Kubernetes, like cloud native solutions like Kubernetes. So picture, like in a picture of world where AI predicts maintenance needs before issue rises and IOT optimizes routes in real time and Kubernetes scales operations seamlessly. This convergence can reduce, reduce operational cost by, up to 30 percent improve vehicle reliability and enhance driver safety. so let's deep dive into this actually. so let's deep dive into that, it actually. So So, how AI is transforming fleet management? if you see the, the current, diagram, and if you see that, you have the company vehicles, let's say if you have a, ambulances, or, maybe, a trucks, like a company will be having trucks, and, the companies will be having, companies like Uber, A any other, any, carpet companies, having their own vehicles, so what happens is, like we need to, obviously like com, fleet manage manager, like fleet managers should able to, see the dashboards, like what's going on, what's going on, with the tire pressures and, vehicle, tire, tire pressures as well as fuel and certain things like a fuel and maintenance like, they have in the dashboards. So based on that they will try to take the decisions of buying the new vehicles or do the maintenance and improve proactive performance measures So we should see in the dashboards actually, you know We should see what's going in the dashboards and we should get an alerts actually that's how it is right now when it comes to like how AI is Revolution in this whole process, so artificial AI is revolutionary revolutionizing We how we manage optimized vehicles. So through advanced Learning algorithms and predictive analysis. So AI enables decision making automobiles complex operation task The transformation is helping fleet managers to reduce costs and improve safety and maximize efficiency At an unprecedented, scale. So it's, so what, it's more of because of algorithms, predictor, by using AI and predictor, AI with predictor algorithms, we can easily, we can, we can easily, we can, we can simplify the decision making and, and automate any complex tasks. so this is about like how, AI transforming fleet management and, next coming to the next slide. so how, So due to the rise of, fleet management, there are two things are happening. One is a predictive maintenance and other thing is, efficiency boost. So when it comes to predictive maintenance, a drives advanced, advancements in, predictive maintenance and reducing vehicle downtime by at least 40% and advanced. and advanced algorithms analyze the engine data to forecast potential issues before it even occurs. So that's a big, that, that's a big, big thing. that, that really big thing when it comes to the, vehicle maintenance. It's and again, it, coming to the efficiency boost AI overall. operational effi, improve the operational efficiency with organizations experience improving, improvements of around 30 percent and smart systems optimizes routes, schedules and, resource allocation real time, like smart systems such as like IOT devices are going to optimize the routes and, schedules and resource allocation real time. So this is really, big change. so IOT internet of, IOT means like internet of things. So how it is, so which is really useful in real time tracking and monitoring. IOT provides three things, like one is enhanced safety and another one is transparency and third one is risk reduction. So when it comes to enhanced safety, IOT enables real time tracking of vehicles and condition, and condition. Monitoring enhancing of, fleet safety and they're coming to say transparency. IOT enabled sensors offer increased transparency. This provides a clear view of fleet operations and it comes to the third thing, a risk reduction. Like now companies using IOT reporting 25 percent decrease in risks. This is due to enhanced monitoring and data. . And, let's, coming to the, third, third key component, which is a Kubernetes. So like in Kubernetes, how, how Kubernetes, powering modern fleet management infrastructure. So we, because we need infrastructure in, IT we need infrastructure and a for running ai, predictor, fleet management. We need, so we need it in edge computing for which is essential. E even in, essentially in even in a fleet management right now, so how fleet care, how a Kubernetes is, revolutionizing this whole process, it is, using, so if you see, so what Kubernetes is doing, it's an underlying, key backbone of all these things, so because if, backbone of these things, so what it is providing So Kubernetes provides a central, containerization and resource management capabilities for robust, robust fleet management systems. And, and, second thing, it comes like automated deployment. See, so Kubernetes, provides seamless scaling, automated deployment of applications and microservices for real time data processing, which is for IoT. And third thing, resource optimization, and has the resource utilization and efficiency management of computing. Resources for AI and IoT operation. And the third thing is it provides security and flexibility, flexibilities. so when it comes to security and flexibility, it isolates environments with an multi environment support. Like a cloud on prem hybrid for secure and adaptable operation, which is very key in fleet care management So when it comes to the scalability kubernetes allows seamless scaling of application microservices that process large volumes of iot data In real time, it's really like IOT data is the key for a fleet management and to get the a real time data Of a vehicle so and when it comes to the deployment it can automate deploy kubernetes can automate deployment Scaling operations in fleet management ensuring that updates and new features are continuously integrated and delivered and also Kubernetes provides resource efficiency. Kubernetes enhances resource utilization by effectively managing computer resources essential for processing AI models and handling IoT data. And the fourth thing is isolation and security. With its containerization feature, Kubernetes provides isolation environments for different applications, enhancing security and reliability. And flexibility. It supports various environments. such as cloud, on prem hybrid and making it adaptable, changing data processing and AI requirements in fleet management. In summary, Kubernetes serves as a backbone for deploying and maintaining robust, scalable, and efficient systems necessary for the dynamic field of IoT and AI driven fleet management. And coming to the success story of AI predicting, breakdowns. So transform, transformative AI integration. Our cutting, like cutting edging, our cutting edge, machine, system revolutionized fleet management by processing an unprecedented, 500, 000 data points from real time vehicle sensors, comprehensive engine diagnostics, and detailed maintenance history. Histories to spot emerging mecha, mechanical issues before they become, critical failures. And second thing is game changing predictive power. By harnessing the power of advanced algorithms, the system delivered an enhanced 90 percent success in forecasting mechanical failures two weeks before they occurred. This breakthrough enabled fleet managers to schedule maintenance strategically, virtually, eliminating unexpected breakdowns and their associated costs. And third thing is dramatic financial impact. The result, spoke volumes. Like organization deploying this AI solution captured an average of 2. 3 million in annual savings. The, the gains came from eliminating emergency repair premiums. Strategical, scheduling maintenance during off peak hours and maximizing vehicle uptime enhanced fleet productivity. Another success story, like IOT, like about IOT, like how IOT improving fuel efficiency. So one is like a vehicle, diagnostics. And second thing is fuel savings. And third thing is a sustainable operations. So when it comes to the vehicle diagnostics, real time IOT sensors monitored, engine performance, deliver, behavior and routing efficiency and leading to, data driven optimization of fleet operations. And then coming to the fuel savings. Implementation resulted 20 percent improvements in fuel efficiency, saving an average of 150, 000 annually per, vehicle, per 100 vehicles while reducing maintenance costs. And, the third thing is, reduce sustainable operation. Reduce carbon emissions by 20 25%, equivalent to removing 50 percent cars from road annually. while meeting, stringent environment compliance standards and coming to the success story of Kubernetes scaling operations when it comes to the fleet care management. seamless deployment, one is seamless deployment and second one is scalability and third one is reliability. when it comes to, seamless, deployment. Kubernetes orchestrates orchestrated flaw a flawless deployment across multiple cloud environments reducing deployment time from Days to minutes while maintaining 99. 99 up time And the second thing is scalability fleet operations scale over 3300 within six months Handling peak loads of 10, 000 concurrent vehicle connections without performance degradation. and third thing is reliability. System maintained 99. 99 percent availability throughout scaling with zero critical incidents and automated failure, failover, ensuring continuous service delivery. The future in, data driven, up to, so the data driven, so the four key pillars like here is optimization, efficiency, safety, and intelligence. optimization is something like continuous improvement through predictive analytics. And, we can, achieve optimization using continuous improvement through predictive analytics. And, efficiency can be achieved by streamlining operations and resolution, resource utilization. And that thing is like we can achieve safety with enhanced risk management and prevention. And fourth thing is intelligence by achieving data driven decision making foundation. The powerful combination of AI and IoT and Kubernetes creates a comprehensive ecosystem for intelligent fleet management. This integration enables real time data analysis, predictive maintenance, and automated decision making. Transforming traditional fleet operations into agile, efficient, and future ready systems. coming to the multi cloud, deployment, so we are three things here, like a flexible cloud strategy. Dynamic scaling, enterprise reliability. so when it comes to flexible cloud strategy, deploy and manage solutions across AWS, Azure, Google platforms, while maintaining united control visibility. And second thing is dynamic scaling. Automatically scale Resources up and down based on demand and ensuring optimal performance while controlling costs and across all cloud environments. And, third one is enterprise reliability. Achieve 99. 99 percent uptime distributed architecture and automatic failover, keeping your operations running smoothly across multiple regions. This is very, this multi cloud deployment is really critical, adaptable in, fleet care management. So coming to the actionable insights and coming to the road map. So three, there are three strategic phases on proven methodology. The methodology deliver results through three focused phases. One is a comprehensive fleet management and second one is a seamless technology deployment. And, third one is continuous performance, optimization. So coming how many days to get success? so experience transformation in just 90 days with, with accelerated implementation program, featuring weekly milestones and, measurable KPI, improvements. And, with this combination of IOT AI and, Kubernetes, we can achieve, success in 90 days itself. And, and, like most of the clients consistently achieve 20 percent improvement in operational efficiency through AI powered automation, real time monitoring, and predictive analytics. And, embraced, transformative technologies like, AI lever, leverage AI intelligent algorithms to optimizing fleet care, fleet management and predict maintenance needs through unprecedented accuracy. So for, and coming to the IOT, transform your fleet with real time vehicle monitoring and data driven insights from. smarter decision making. And third one is Kubernetes. Build resilient, scalable infrastructure that adapts to growing your fleet while ensuring seamless data management. key takeaways and next steps. The powerful combination of AI, IoT and Kubernetes create a transformative foundation for moderate fleet management. Delivering, predictive maintenance, real time monitoring, and scalable operations. Begin your digital transformation journey by identifying key pain points, selecting pilot projects, and improving these technologies in phases to ensure sustainable success. Organizations can embrace these innovations now will gain significant competitive advantage through improved efficiency, reduced cost, and enhanced safety metrics. And, thank you for, attending my, session for, about this fleet care, management, along with IoT, Kubernetes and, AI. Thank you.