# US 12,764,443 B2 · Systems and methods for telemetry data compression

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- Number: US 12,764,443 B2
- Document ID: US12764443B2
- Status: Granted
- Kind: B2
- Application number: 18/743,131
- Filed: 2024-06-14
- Published: 2025-12-18
- Granted: 2026-10-13
- Earliest claimed: 2024-06-14
- Assignees: Atombeam Technologies Inc.
- Applicants: AtomBeam Technologies Inc.
- Inventors: Zhu Li; Paras Maharjan
- Web page: https://patentgrep.com/patent/US12764443B2

## CPC

- H04Q 9/00: Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
- G06N 3/0455: Auto-encoder networks; Encoder-decoder networks
- H03M 7/40: Conversion to or from variable length codes, e.g. Shannon-Fano code, Huffman code, Morse code
- H03M 7/70: {Type of the data to be coded, other than image and sound}
- H04Q: SELECTING (switches, relays, selectors H01H; wireless communication networks H04W)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- H03M: CODING; DECODING; CODE CONVERSION IN GENERAL (using fluidic means F15C4/00; optical analogue/digital converters G02F7/00; coding, decoding or code conversion, specially adapted for particular applications, see the relevant subclasses, e.g. G01D, G01R, G06F, G06T, G09G, G10L, G11B, G11C, H04B, H04L, H04M, H04N; ciphering or deciphering for cryptography or other purposes involving the need for secrecy G09C)

## Abstract

A system and method are disclosed for compressing and restoring data. The system includes a computing device comprising at least a memory and a processor, and a telemetry encoding module comprising programming instructions stored in the memory and operable on the processor. The instructions cause the computing device to compress telemetry data to create compressed telemetry data and generate a bitstream of the compressed telemetry data. A telemetry decoding module includes programming instructions stored in the memory and operable on the processor that cause the computing device to receive the bitstream of compressed telemetry data and apply the bitstream of compressed telemetry data as input to the telemetry decoding module. The bitstream can be decompressed to generate a reconstructed version of the telemetry data to conserve important resources such as network bandwidth and storage.

## Claims

### Claim 1

A system for compressing and restoring data, comprising:
a computing device comprising at least a memory and a processor;
a telemetry encoding module comprising a first plurality of programming instructions stored in the memory and operable on the processor, wherein the first plurality of programming instructions, when operating on the processor, cause the computing device to:
receive and tokenize telemetry data;
generate probability distributions for tokens of the telemetry data using a transformer-based neural network (TBNN);
rank the tokens according to the generated probability distributions;
perform lossless compression of the tokens based on the ranking of the tokens to create compressed telemetry data; and
generate a bitstream of the compressed telemetry data;
a telemetry decoding module comprising a second plurality of programming instructions stored in the memory and operable on the processor, wherein the second plurality of programming instructions, when operating on the processor, cause the computing device to:
receive the bitstream of the compressed telemetry data;
apply the bitstream of compressed telemetry data as input to the telemetry decoding module; and
decompress the bitstream of compressed telemetry data to generate a reconstructed version of the telemetry data.

### Claim 2 (depends on 1)

The system of claim 1, wherein the telemetry encoding module further comprises programming instructions that when operating on the processor, cause the processor to perform the lossless compression using arithmetic coding.

### Claim 3 (depends on 1)

The system of claim 1, wherein the telemetry encoding module further comprises programming instructions that when operating on the processor, cause the processor to perform the lossless compression using Huffman coding.

### Claim 4 (depends on 1)

The system of claim 1, wherein the telemetry encoding module further comprises programming instructions that when operating on the processor, cause the processor to perform the lossless compression using block-sorting compression.

### Claim 5 (depends on 1)

The system of claim 1, wherein the telemetry encoding module further comprises programming instructions that when operating on the processor, cause the processor to perform the lossless compression using dictionary-based compression.

### Claim 6

A method for compressing and restoring data, comprising steps of:
receiving and tokenizing telemetry data;
generating probability distributions for tokens of the telemetry data using a transformer-based neural network (TBNN);
ranking the tokens according to the generated probability distributions to generate rank values;
perform lossless compression of the tokens based on the ranking of the tokens to create compressed telemetry data;
generating a bitstream of the compressed telemetry data;
applying the bitstream of compressed telemetry data as input to a telemetry decoding module; and
decompressing the bitstream of compressed telemetry data to generate a reconstructed version of the telemetry data.

### Claim 7 (depends on 6)

The method of claim 6, wherein performing lossless compression comprises performing arithmetic coding.

### Claim 8 (depends on 6)

The method of claim 6, wherein performing lossless compression comprises performing Huffman coding.

### Claim 9 (depends on 6)

The method of claim 6, wherein performing lossless compression comprises performing dictionary-based compression.

### Claim 10 (depends on 6)

The method of claim 6, wherein performing lossless compression comprises performing block-sorting compression.
