Distributed intelligence network for AI-driven device collaboration and task delegation

Abstract

A decentralized artificial intelligence network that enables device-to-device collaboration, task delegation, and privacy-preserving AI learning across multiple connected devices without reliance on a

Claims

A distributed intelligence network, wherein Al-capable devices communicate and share Al tasks without reliance on a centralized cloud infrastructure, thereby enabling local and collaborative processing of artificial intelligence workloads.A real-time task delegation sydtem, wherein Al workloads are dynamically assigned to devices in the network based on their processing capacity, power availability, and computational efficiency.A decentralized privacy-preserving Al learning system, wherein devices collaboratively train and optimize Al models using federated learning techniques, ensuring that raw data remains local to the devices.A security mechanism for distributed intelligence networks, comprising encryption methods and anomaly detection systems to prevent unauthorized access, data breaches, and task manipulation.Avision-based system for collaborative Al task sharing, wherein connected cameras within the network detect patterns, anomalies, and events in real time by sharing processing power and insights.An autonomous technology optimization framework, wherein autonomous vehicles or devices share real-time intelligence, including traffic data or navigation instructions, to improve decision-making, safety, and efficiency.