Edge Artificial Intelligence

Grab the future of computing with Edge Artificial Intelligence, a practical and forward-looking guide by Parikshit Mahalle. This book cuts through theory to show how AI is migrating from the cloud to the edge—delivering lower latency, improved privacy, and energy-efficient intelligence for real-world devices.

Inside, readers will find clear explanations of edge AI fundamentals—edge architectures, on-device machine learning, model compression, and hardware-software co-design—paired with industry-relevant case studies across IoT, autonomous vehicles, smart cities, healthcare, and industrial automation. Step-by-step discussions on deployment strategies, security and privacy best practices, and performance optimization make complex concepts accessible to engineers, data scientists, and decision-makers alike.

Whether you’re in Bengaluru, London, San Francisco, or emerging tech hubs across Asia and Europe, this book connects global trends to local implementation. Practical insights into frameworks, embedded systems, sensor integration, and energy-aware model design help teams reduce latency, cut bandwidth costs, and scale AI to constrained devices.

Ideal for professionals, researchers, and advanced students focused on edge computing, embedded AI, or IoT development, Edge Artificial Intelligence helps you move projects from prototype to production. With a balanced blend of theory, hands-on guidance, and future-looking perspectives, Parikshit Mahalle equips readers to architect robust, secure, and efficient edge solutions.

Choose a resource that speaks the language of modern deployment and real-world constraints—add Edge Artificial Intelligence by Parikshit Mahalle to your shelf and start building the next generation of intelligent edge applications.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.