Smartphone-based NFC for real-time food spoilage detection and traceability

Thesis Abstract

This study investigates how smartphone-based near-field communication (NFC) technologies can enable real-time detection of food spoilage and enhance traceability across the supply chain, addressing persistent post-harvest losses, consumer safety concerns, and opacity in provenance. The problem centers on delays in spoilage identification, inconsistent data capture, and fragmented traceability systems that impede timely decision-making and risk mitigation. The aim is to develop and validate an NFC-enabled framework that integrates sensor-enabled packaging, a mobile application, and cloud-based analytics to provide instantaneous spoilage indicators and end-to-end traceability. Specific objectives include (1) designing NFC tags with embedded time-temperature indicators (TTIs) and volatile organic compound (VOC) sensors tailored for perishable commodities such as leafy greens and fresh fruits; (2) developing a mobile app interface that reads NFC tag data, stores immutable records, and triggers alerts based on predefined spoilage thresholds; (3) constructing a cloud-based analytics pipeline incorporating regression models and anomaly detection to infer spoilage risk from multi-parameter sensor streams; (4) evaluating user acceptance and workflow impact among supply chain actors through a mixed-methods assessment; and (5) assessing the system’s effectiveness for traceability by comparing NFC-enabled records with conventional bar-code and batch-level data. The methodology adopts an explanatory mixed-methods design. The population comprises producers, distributors, retailers, and consumers within a regional perishable-food supply chain. A stratified random sample of 200 primary producers, 60 distributors, 40 retailers, and 300 consumer participants will be recruited. Data collection will combine (i) quantitative measurements from NFC-tagged samples (n=1,000 items across two commodity groups) including TTIs, temperature logs, and VOC sensor readings; (ii) app-generated interaction data, spoilage alerts, and timestamped events; and (iii) qualitative inputs from interviews and focus groups with 40 stakeholders. Instruments include calibrated NFC-TTI tags, a smartphone application with secure authentication and cloud synchronization, a standardized questionnaire for usability assessment, and interview guides aligned with technology acceptance theory. Validity and reliability will be ensured through pilot testing (n=50 items), test-retest reliability checks of sensor readings (Cronbach’s alpha targets ?0. eighth), and triangulation of sensor data with laboratory reference analyses. Data analysis will employ (i) descriptive statistics to characterize spoilage indicators and event frequencies; (ii) regression analysis to quantify relationships between sensor variables (TTI, temperature, VOC levels) and microbial spoilage endpoints; (iii) time-series analysis to detect spoilage trajectories and early warning signals; (iv) ANOVA or MANOVA to examine differences in performance across commodity types and stakeholder groups; (v) thematic analysis of qualitative data to elucidate perceived usefulness and adoption barriers; and (vi) a conceptual model testing the effect of perceived usefulness and ease of use (as per Technology Acceptance Model extended with Trust and Perceived Risk) on adoption intention. The study’s expected findings include (a) a robust correlation between NFC-tag sensor data and spoilage status validated against conventional microbiological assays; (b) improved detection of spoilage onset and reduced decision latency for interventions; (c) enhanced traceability with immutable, auditable event logs across the supply chain; and (d) positive user acceptance among stakeholders when the system demonstrates tangible reductions in waste and cost. The contribution to knowledge encompasses an integrated NFC-based spoilage detection and traceability framework, novel use of TTIs and VOC sensing within NFC tags for real-time monitoring, and a data analytics pipeline combining regression, time-series, and anomaly detection within supply chain contexts. The study concludes that smartphone-based NFC data fusion can transform post-harvest management by enabling proactive spoilage mitigation and transparent provenance. Recommendations include standardization of NFC tag specifications for perishable commodities, scalability considerations for large-volume supply chains, integration with existing ERP systems, and policy guidance to promote NFC-enabled traceability adoption and data interoperability.