18255291. COMPRESSION OF MULTIMODAL SENSED SIGNALS simplified abstract (Eaton Intelligent Power Limited)
Contents
- 1 COMPRESSION OF MULTIMODAL SENSED SIGNALS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 COMPRESSION OF MULTIMODAL SENSED SIGNALS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
COMPRESSION OF MULTIMODAL SENSED SIGNALS
Organization Name
Eaton Intelligent Power Limited
Inventor(s)
Daniel Zucchetto of Dublin (IE)
Johannes Van De Belt of Dublin (IE)
Niall Cahill of Dublin 15 (IE)
COMPRESSION OF MULTIMODAL SENSED SIGNALS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18255291 titled 'COMPRESSION OF MULTIMODAL SENSED SIGNALS
Simplified Explanation
The patent application describes a method for compressing and transmitting data between an edge device and a remote server using wavelet transform and autoencoder techniques.
- Collect data at the edge device attributed to multiple signal signatures
- Generate a data matrix at the edge device
- Transform the data matrix using wavelet transform
- Compress the data using an autoencoder
- Transmit the encoded compressed data to the remote server
- Decompress the data at the remote server using an autoencoder
- Reconstruct the signal signatures using an inverse wavelet transform
- Store the reconstructed data signatures in a datastore on the remote server
Potential Applications
This technology can be applied in various fields such as IoT devices, sensor networks, and data transmission systems where efficient compression and transmission of data is required.
Problems Solved
1. Efficient compression and transmission of data between edge devices and remote servers. 2. Reconstruction of signal signatures accurately at the remote server.
Benefits
1. Reduced bandwidth usage for data transmission. 2. Improved data compression and reconstruction techniques. 3. Enhanced data storage and retrieval capabilities.
Potential Commercial Applications
Optimizing data transmission in IoT devices Enhancing sensor networks for efficient data processing and storage
Possible Prior Art
Prior art in data compression and transmission methods using wavelet transform and autoencoders may exist in the field of signal processing and communication systems.
Unanswered Questions
How does this method compare to existing data compression techniques in terms of efficiency and accuracy?
The article does not provide a direct comparison with other data compression techniques to evaluate the performance of this method.
What are the potential limitations or challenges in implementing this technology on a large scale?
The article does not address the scalability or practical challenges that may arise when deploying this technology in real-world applications.
Original Abstract Submitted
There is provided a data transmission and compression method arranged to compress and transmit data between an edge device and a remote server. The method comprises collecting data at the edge device, wherein the data is attributed to a plurality of signal signatures; generating a data matrix at the edge device; transforming the data matrix, wherein transforming the data comprises using a wavelet transform; compressing the data, wherein compressing the data comprises utilising an autoencoder; and transmitting the encoded compressed data to the remote server via a communication channel. The method further comprises, at the remote server, decompressing the data utilising an autoencoder; reconstructing the signal signatures using an inverse wavelet transform; and storing the reconstructed data signatures in a datastore on the remote server.
