Food Security Discussion SeriesMichael Godfrey research drone for beneficial bug delivery
Technology and Food Security – Mixing and Matching Needs
Summary by Dr Jane O'Sullivan

Thursday, 17 Nov 2016
A/Prof. Kim Bryceson

New technologies are conceptualised in a range of “buzz phrases” from “the internet of things” and “Big Data” to “eLandscape of business” and “Smart Agriculture” but few of us recognise the connections between these innovations and our food challenges. To a significant extent, emerging technologies will underpin the capability of the world to deliver a food secure future.

There are many factors contributing to food insecurity and several avenues through which they are addressed. The main avenues to which emerging data systems are contributing are Smart Production (more productive with less impact), Smart Logistics (agrifood supply chains) and Health and Nutrition (quality control and biosecurity). The miniaturisation and automation of monitors of a wide range of parameters, the networks that connect them with analysis, and automated feedback systems responding to the data, are rapidly opening new opportunities for system optimisation and risk minimisation.

Precision agriculture refers to systems to tailor the management of crop and soil to match the conditions at each location in a field from year to year, reducing spatial variability. This is an area that has been developing for several decades, but is taking an exponential leap with the application of new inexpensive, unobtrusive monitors to generate much richer data and to control more finely tailored management responses.

The UQ Gatton agritech lab has been particularly involved in drone technology. Drones allow much finer spatial and temporal precision than satellite imaging, as well as enabling monitoring of parameters not detectable at greater distance (like the location of individual livestock via RFID tags). Where GPS used to be relatively expensive, heavy and energy-hungry, these days they are in every mobile phone. They are light enough to combine with other sensors and transmitters on a drone, and cheap enough that the drone’s vulnerability to damage is not an impediment to its usefulness – nor to letting students muck around with them, exploring and debugging innovative applications. The drones must be under 2 kg to avoid the need to register its movements as an aircraft with CASA. Most recent UQ models are around a kilogram. Data can be downloaded to a computer or mobile phone. Images from multispectoral cameras can be compiled into a high-resolution field image. These may be visible light, infra-red, or specific colours such as detecting where tomatoes are ripe in a field, or the presence of specific weeds. One student project has used drones to release beneficial bugs across a field and to monitor their impact.


The “internet of things” refers to a network of physical objects that contain technology to sense and/or interact with their environment, and to transfer data over a network without requiring human-to-human or human-to-computer interaction. Under the Smart Campus Initiative, the UQ Gatton campus and farm now has a multisensor mesh recording data to the cloud on a wide range of biophysical variables, relevant to water quality, soils crops and livestock, and weather and environment. For example, wireless solar-powered cameras monitor pregnant mares, avoiding the need for students to stay up with them all night awaiting foaling. Nodes in the wireless sensor network automatically reroute information if one node drops out. The system can allow remote control of pumps, gates and other devices. A lot of design development has gone into making the installations robust against damage by livestock, birds and weather. The sensors and nodes are supplied by Libelium, a Spanish tech company. In addition to the research at UQ, a number of universities in USA, Netherlands and elsewhere are also developing food systems applications.

Robotics are another area of rapid innovation. Agricultural uses range from automated dairies to harvesting applications.

The “Big Data” generated by these systems poses challenges to capture, store, clean, query, analyse and visualise the data. Some of this can be done by the devises, some by people.

Big Data is now big business: there is a vast array of companies innovating and providing services and technology in this space. The use of various “e-Tools” to serve various business functions is referred to as the “e-Landscape of business”. Businesses are increasingly dependent on society-wide service providers and regulatory systems to implement these tools. “E-Readiness” refers to the extent to which countries (particularly developing countries) have capacity to support these systems, the lack of which is an increasing impediment to business.

There are a number of global analysis frameworks, which collect data to track progress on food security, to identify incidents and causes of food insecurity and to inform responses. These include the FAO’s Global Information and Early Warning System on Food and Agriculture (GIEWS), World Food Program’s Vulnerability Analysis Mapping (VAM), the FAO’s Food Insecurity and Vulnerability Mapping System (FIVIMS) and USAID’s Food Security Framework (FSF). These systems are compromised by the often poor quality of data. New real-time monitoring and data collection systems will greatly improve the quality and timeliness of the data in these frameworks. They are also improving forecasting of the food supply impacts of droughts and other weather disruptions, and of conflict or natural disasters. As these systems develop further, the information will become increasingly accessible and versatile for a wider range of stakeholders, from national policy makers to rapid response agencies and developers of longer-term strategic interventions.

The accelerated pace of development of so many of these synergistic and interdependent threads of information and automation technology are creating a digital disruption in agriculture. Who knows – maybe young people will start taking up farming again.

Download A/Professor Bryceson's 17 Nov presentation as a PDF (6 MB).

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