Abstract
In this article, we discuss our experience of realising a prototype IoT-based food safety monitoring solution which integrates inexpensive off-the-shelf open source IoT technology for monitoring food deliveries, semantic services for managing and reasoning about food safety provenance records, and private blockchain networks for persistent and secure storage of semantic provenance graphs. We describe how observation of real-world contexts was used to develop a prototype device, and the results of field trials deploying these prototypes as part of the food delivery process. Results indicate that continuous, context sensitive, trustworthy temperature measurement could provide benefits to multiple stakeholders across the delivery pathway. However, close attention has to be paid to the technology used - as cheap multi-functional IoT devices may produce low quality sensor observations which adversely affect the utility of the overall solution. Our experience also suggests that future food safety management systems may need to include machine-processable guidelines to support analysis of raw sensor data for food safety compliance.
Highlights
In recent years, the advent of affordable Internet of Things (IoT) devices has enabled a number of novel data-driven innovations across many industries (Farooq et al, 2015)
We argue that a similar approach could be applied to the food delivery domain, which would encompass firstly capturing what is expected to happen during the delivery process so it can be later linked with the provenance of the actual delivery process
The outside stage when food was removed from the cold store and subsequently placed in the delivery van was not detected by the IoT monitor
Summary
The advent of affordable Internet of Things (IoT) devices has enabled a number of novel data-driven innovations across many industries (Farooq et al, 2015). .” Many businesses today address this through a series of manual tasks (e.g., temperature checks of perishable items using manual probes) and paper based record keeping following the procedures defined in their HACCP food safety management systems (Mortimore and Wallace, 2013). Such systems consist of three components: (awareness of) hazards, control measures, and critical control points. There is a clear opportunity for automation of temperature measurements and other environmental sensing through IoT at various critical control points (e.g., while food is stored in a fridge) defined in HACCP plans (Tian, 2017) For chilled food to be considered safely stored, normally the temperature must be no higher than 5◦C to eliminate microbiological growth (the hazard) (Food Standards Agency, 2016). 5◦C is the “critical limit.” There is a clear opportunity for automation of temperature measurements and other environmental sensing through IoT at various critical control points (e.g., while food is stored in a fridge) defined in HACCP plans (Tian, 2017)
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