Sustainability in Computer Vision: A Review of the State of the Art

Contextualization
Computer Vision has become one of the key pillars within the field of Artificial Intelligence. However, one of the major challenges in this area is the high energy consumption associated with the processing and training of models. This issue has sparked growing interest in analyzing and optimizing the energy resources utilized by this technology. Therefore, it is necessary to conduct a comprehensive review of the state of the art on the energy impact of computer vision and explore potential solutions to make it more sustainable.
he primary objective of this thesis is to conduct a thorough review of the current state of sustainability in the field of computer vision. Specifically, the aims include:
1. Assess Energy Consumption
2. Identify Optimization Techniques.
3. Evaluate Sustainable Practices
4. Propose Future Directions.
5. Impact Assessment.

Key areas of focus:
- The environmental impact of image recognition techniques within computer vision
- The energy consumption associated with these techniques
- Waste management considerations in the development and deployment of computer vision technologies

Ideal skills and experience for the job:
- Understanding of sustainability issues, particularly in relation to technology
- Excellent research and literature review skills
- Ability to synthesise complex information into clear, concise assessments
- Strong understanding of energy consumption and waste management in a tech context.