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Emerging Integrating Approach to Sensors, Digital Signal Processing, Communication Systems, and Artificial

Aleš Procházka1,2, Oldřich Vyšata3, Hana Charvátová4

  • 1Department of Mathematics, Informatics and Cybernetics, University of Chemistry and Technology in Prague, 160 00 Prague, Czech Republic.

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This summary is machine-generated.

Digital signal processing (DSP) and artificial intelligence (AI) offer a unified approach for analyzing sensor data across various fields. Integrating DSP with AI enhances research, education, and the development of new digital technologies.

Keywords:
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Area of Science:

  • Engineering and Technology
  • Computer Science
  • Data Science

Background:

  • Autonomous sensor systems are central to modern technology, enabling data acquisition through wireless communication.
  • Interconnecting sensors and advanced signal analysis are crucial for both theoretical learning and practical problem-solving.

Purpose of the Study:

  • To highlight the common mathematical foundations for processing diverse sensor data.
  • To demonstrate the integration of Digital Signal Processing (DSP) and Artificial Intelligence (AI) across various applications.

Main Methods:

  • Emphasizing a unified mathematical framework for signal processing.
  • Integrating DSP and AI methods for data analysis.
  • Utilizing case studies involving sensor technology, computational methods, and visualization.

Main Results:

  • DSP and AI integration enables the application of similar computational methods in fields like robotics, digital twins, and augmented reality.
  • Case studies show that combining sensor technology with shared computational approaches fosters interdisciplinary collaboration.
  • The integration supports innovative research and teaching strategies in the digital era.

Conclusions:

  • Integrating AI with DSP provides a common platform for diverse research and educational pursuits.
  • This integration redefines the educational role in the digital era and drives the development of new digital technologies.
  • The approach strengthens interdisciplinary collaboration through shared methodologies and case studies.