Adaptive real-time multi-modal compression system with dynamic resource allocation

A system for adaptive real-time multi-modal compression with dynamic resource allocation, comprising:

• a computing device comprising a processor and a memory;
• a plurality of programming instructions stored in the memory which, when operating on the processor, cause the computing device to:
• continuously monitor device resource state comprising battery level, CPU utilization, and memory availability;
• classify multi-modal input data streams to determine priority levels, wherein the multi-modal input data comprises at least two data types selected from image data, audio data, text data, and sensor data;
• determine optimal compression parameters by executing multi-objective optimization that balances compression efficiency, reconstruction quality, and energy consumption while satisfying resource availability constraints;
• compress the multi-modal input data using an adaptive variational autoencoder comprising an encoder network with dynamically selectable processing complexity, a unified latent space representation with adjustable dimensionality, and a decoder network;
• automatically switch between operational modes based on the monitored device resource state, including an emergency mode that applies maximum compression settings when resources fall below predetermined thresholds;
• and
• adapt compression parameters based on observed performance outcomes to improve future optimization.