Evaluating Knowledge Creation in Smart Container for Monitoring and Prediction of Fresh Fruit Quality: A Systematic Literature Review
Post-harvest fruit losses continue to exceed 30% in many emerging economic. While smart containers equipped with Internet-of-Things (IoT) sensors and artificial-intelligence (AI) models can mitigate spoilage, most systems treat data as an end in itself rather than as a raw material for knowledge creation (KC). Applying PRISMA-2020 and bibliometric mapping (VOSviewer & Bibliometrix), we screened 343 Scope records (2003-2025) and analysed 43 primary studies. The key finding is that more than 70% of the literature operationalises only the Combination phase of the SECI model (data aggregation and predictive modelling). Socialization (tacit knowledge sharing) and Internalization (experiential learning) are almost absent, thereby limiting adaptive decision-making and stakeholder engagement. We conclude with a research-practice roadmap that embeds the complete SECI cycle into smart- container design.
Authors
- Taufik Djatna (ORCID: https://orcid.org/0000-0002-2071-089X)
- Sri Hartati Yuliani (ORCID: https://orcid.org/0000-0001-5246-8252)
- Endang Warsiki
- Encik Eko Rifkowaty
Institutions
- IPB University (ID)
- Universitas Muhammadiyah Kupang (ID)
- National Nuclear Energy Agency of Indonesia (ID)
- Politeknik Kesehatan Kemenkes Semarang (ID)
- National Research and Innovation Agency (ID)
Publication Details
- Journal
- BIO Web of Conferences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1051/bioconf/202518903002
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Lembaga Pengelola Dana Pendidikan