PreMeSS (Predicting Meat Supply System):

With African Swine Fever (ASF) prevalence and bird flu cases in the region, public health and safety are always at risk, and partnered with inadequate disease outbreak management, meat products may be unjustly recalled, resulting in financial losses and harm to the industry's reputation.

Meat Product Traceability from Farm to Market

A team of Computer Engineering professionals spearheaded by Engr. Jetron Adtoon is implementing a DOST-funded project that promotes transparency and consumer confidence in our meat products. Officially entitled “PreMeSS (Predicting Meat Supply System): A Decision Support System for Forecasting Meat Supply in Davao City using Geospatial and Predictive Analytics for National Meat Inspection Services RTOC XI,” this project marks a significant advancement in the digitization of the meat supply chain. While the core of PreMeSS lies in its innovative use of geospatial and predictive analytics to forecast meat supply dynamics accurately, it also integrates a farm-to-market traceability system. From the livestock point of origin to delivery to slaughterhouses, health and condition assessment, slaughter processes, antemortem and post-mortem inspection (removing any parts unfit for consumption), and packaging to distribution are all recorded.

Digitalization of NMIS Processes

This system encompasses the entire process flow of National Meat Inspection Services in dealing with its stakeholders: meat transport vehicle profiling, farm owner/slaughterhouse profiling, meat inspector functions (checking of standard documents, generating certificates, inspecting meat quality, generating shipping permits), from antemortem to post-mortem stages, digitizing each step to ensure comprehensive traceability and data accuracy. PreMeSS aims to revolutionize monitoring and managing meat products by integrating advanced technologies. This endeavor is in partnership with the National Meat Inspection Services Regional Technical Operation Center XI (NMIS RTOC XI) headed by Dr. Lailanie Rose P. Rico under the Department of Agriculture.

Forecasting Meat Supply Chain

Through advanced data technologies, PreMeSS features (1) Geospatial Analytics presenting the geographic distribution of meat production, including mapping and analysis of meat distribution activities, and (2) Predictive Analytics, which integrates several machine learning models (k-NN algorithm, logistic regression analysis, decision tree, and J48) based on historical data and market trends, allows future meat supply and demand forecasts.

Benefits and Potential Application

Economic Impact

The implementation of PreMeSS is poised to bring substantial economic benefits. By accurately forecasting meat supply, the system helps optimize resource allocation, reducing waste and ensuring a steady supply of meat products to meet consumer demand. Additionally, the enhanced traceability and transparency of the meat supply chain boost consumer confidence, likely leading to increased sales and market growth. Small and medium-sized enterprises (SMEs) in the meat sector, particularly in Davao City, stand to gain from improved market stability and access to valuable data insights, driving local economic development.

Social Impact

PreMeSS significantly enhances food safety and quality on the social front, benefiting public health. The system's comprehensive traceability ensures that consumers can access detailed information about the meat they purchase, fostering trust and empowering informed decision-making.

Ways Forward

The PreMeSS project holds promising advancements and impacts. Predictive analytics will become increasingly refined as the system matures, fueled by tremendous historical data. At its conception, PreMeSS was first considered in Davao City and its neighboring provinces. Successful implementation will lead to adaptation to other regions, scaling its benefits nationwide.