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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM.FCE010

ECHOVAULT: SMART EMOTIONAL JOURNALING AND MEMORY PRESERVATION PLATFORM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM.FCE010

Volume:

10 |

6 |

Jun 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem.FCE010

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

HP

HARISHA PAL

Department of Civil Engineering,

Faculty of Engineering and Technology, Jain University, Bangalore

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BS

BABASAHEB SAPUTLE

Department of Civil Engineering,

Faculty of Engineering and Technology, Jain University, Bangalore

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DAK

DASARATHY A K

Department of Civil Engineering,

Faculty of Engineering and Technology, Jain University, Bangalore

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Abstract

Keeping track of personal memories and emotional experiences has always been a challenge in the digital age. While people routinely share their thoughts across social media, messaging apps, and note-taking tools, these records tend to be fragmented, disorganised, and poorly secured. EchoVault is a proposed platform that tries to address this gap by combining AI-powered journaling with robust memory preservation techniques. The system uses Natural Language Processing (NLP) to pick up on the emotions embedded in a user’s journal entries, and draws on blockchain-inspired security mechanisms to keep those memories intact and tamper-proof over time. Users can interact through a conversational interface, track how their mood shifts over weeks or months, compose messages to their future selves, and revisit memories through an intelligent retrieval system. This paper outlines the motivation behind EchoVault, surveys the relevant literature, describes the proposed architecture, and discusses where the platform could go from here.

KEYWORDS

Emotional journaling Artificial Intelligence Natural Language Processing Blockchain Mood tracking Memory preservation Digital wellness

Cite This Article

HARISHA PAL, BABASAHEB SAPUTLE, DASARATHY A K, "ECHOVAULT: SMART EMOTIONAL JOURNALING AND MEMORY PRESERVATION PLATFORM," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-5, Jun 2026. https://doi.org/10.55041/ijsrem.FCE010

Full Article/Conclusion

This paper has presented EchoVault, a conceptual platform that brings together AI-driven journaling, NLP-based emotion analysis, and blockchain-inspired data security in service of personal emotional memory. The system addresses a gap in current digital tools: the absence of a unified, intelligent, and trustworthy space for long-term personal reflection. The literature review makes clear that the individual technologies EchoVault draws on are well-established. What is new is their combination in a user-centred platform designed specifically for emotional journaling and memory preservation. The proposed system is intended not just as a technical exercise, but as a tool that could genuinely help people understand themselves better over time. Future work will focus on building and evaluating a working prototype, conducting user studies to assess the quality of the emotion analysis and the usability of the interface, and iterating on the design based on real-world feedback. The potential applications in digital wellness and emotional AI make this a worthwhile direction to pursue.

References

[1] Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017). Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Mental Health, 4(2), e19. [2] Inkster, B., Sarda, S., & Subramanian, V. (2018). An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being: Real-World Data Evaluation Mixed-Methods Study. JMIR mHealth and uHealth, 6(11), e12106. [3] Mohammad, S. M., & Turney, P. D. (2013). Crowdsourcing a Word-Emotion Association Lexicon. Computational Intelligence, 29(3), 436–465. [4] Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT 2019, 4171–4186. [5] Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Retrieved from https://bitcoin.org/bitcoin.pdf [6] Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016). MedRec: Using Blockchain for Medical Data Access and Permission Management. Proceedings of the 2nd International Conference on Open and Big Data (OBD), 25–30.

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Publication Date

6/18/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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