Abstract
This paper looks at some of the challenges associated with data acquisition in VR and AR environments, principally by incorporating the privacy of digital forensic and sensor technology. While VR and AR technologies are mainly seen as providing an immersive experience, they also pose significant challenges in collecting data and protecting data collected in environments for privacy. It will look into advanced sensor technologies of high-resolution cameras, inertial measurement units, and biosensors for data accuracy and efficiency. This further researches the methods of data fusion, in particular, Kalman filtering and machine learning-based fusion. Lastly, the role of edge computing in local data processing to reduce the demands for latency and bandwidth is analyzed to allow for real-time processing. It also discusses privacy-enhancing technologies, such as differential privacy and homomorphic encryption, to ensure the protection of user data while maintaining ethical standards. The present article is aimed at implementing a comprehensive framework integrating these technologies to address both technical and moral problems associated with data acquisition through VR and AR for secure and efficient application in these fields.