| Autor: |
Miguel Amaral, Gabriel Signoretti, Marianne Silva, Ivanovitch Silva |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
SoftwareX, Vol 26, Iss , Pp 101747- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2352-7110 |
| DOI: |
10.1016/j.softx.2024.101747 |
| Popis: |
The Tiny Anomaly Compression (TAC), a vital component of the Python package Conect2AI, is engineered for real-time data compression in Internet of Things (IoT) devices. TAC is an innovative data compression algorithm that leverages the concept of data eccentricity, operating without the need for pre-established mathematical models or assumptions about the underlying data distribution. Furthermore, it utilizes recursive equations, enabling efficient computation with low computational overhead, thereby minimizing memory usage and processing power requirements. This approach renders TAC particularly suitable for resource-constrained environments such as IoT devices, offering an effective and optimized solution for data compression in large volumes and continuous data scenarios. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
