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Slide 1 2016 Seminar Series - Nov 17 2016
Technology and Food Security -
Mixing and Matching needs Kim Bryceson
The University of Queensland Australia
Slide 2 2016 Seminar Series - Nov 17 2016
The Question
The Internet of Things, Big Data, Drone technology, Smart Agriculture, the “eLandscape” of business, Cold Chain Logistics, - how do these “Buzz” phrases that encompass a vast array of different technologies have anything to do with Food Security? Underpin the capability of the world to deliver a Food Secure future
Slide 3 2016 Seminar Series - Nov 17 2016
This Talk
Emerging technologies that are currently being used and are likely to be used in the future for investigating and developing solutions for managing Food INSecurity
Thus leading to the goal of Food Security
Slide 4 2016 Seminar Series - Nov 17 2016
Food Security vs Food INsecurity
Food security: exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food • Food is available • Food is affordable • Food Is utilized
Food INsecurity: is about hunger – that is, only having irregular access to safe, nutritionally adequate, culturally acceptable food from non-emergency sources. • What factors contribute to food
insecurity? • How many people do not have
enough to eat? (ie how many are food insecure?)
• Where do they live? • How could one describe these
countries? (think about their economic, social, political and environmental conditions)
Slide 5 2016 Seminar Series - Nov 17 2016
What contributes to Food INsecurity?
Trade
Population and Urbanisation
Disasters and Conflicts
The Need for Gender Equity
Water, Environment and Climate Change
Poor Health
Poverty
Slide 6 2016 Seminar Series - Nov 17 2016
Addressing these issues?
Smart Production - Improving Food
Production Sustainably
Agrifood Supply Chain/Network
Management and Capability
Development Distribution of
Food resources (Smart Logistics)
Health (Nutrition - link to Smart Agriculture)
Economic Growth Recognising the Role of Women Food Aid
Technology, Multidisciplinary, Long term Education / Capacity Development
Slide 7 2016 Seminar Series - Nov 17 2016
Food Production Challenges
A soaring global population – We need to feed more with less resources
– Food production must become smarter
– Production must be sustainable = Education, Knowledge , Young people
Agriculture is difficult to get young people into – Perceived as labour intensive and non-academic and no $
Technology is pervasive – Miniaturisation of electronics & automation are key drivers of innovation
– Can we harness to engage and develop the new skills needed in Ag?
Slide 8 2016 Seminar Series - Nov 17 2016
Implications & Needs
• Need smart science to address production and associated sustainability issues
• Need specialist skills to feed the world
• Must use new technologies
Slide 9 2016 Seminar Series - Nov 17 2016
Specialist Skills Growing things
– Production (commodity crops, livestock, intensive & organic production )
– Animal Science (physiology, nutrition, reproduction, husbandry etc)
– Animal Health & Welfare
– Vet Science
– Plant Science (crop/pasture physiology, nutrition, genetics etc)
– Soils (chemistry, physics & soils management)
– Chemical management (fertilisers, herbicides, pesticides)
– Managing spatial variability (of the land, pest & weed management, water management)
– Managing sustainability (carbon footprint)
– Technology (machinery, Precision Agriculture - RFID, GPS, IoT etc )
Agribusiness
– Industry Supply Chains (grain, meat, dairy, nuts, fruit & veg, honey, cotton, wool, beverages etc)
– Processing (functional & specialty ingredients)
– Manufacturing (product development)
– Distribution & Logistics (transport & refrigeration)
– Marketing & Branding (market, consumer research)
– Retail (food packaging, sales, food safety & traceability)
– Finance & Risk Management
– Exporting
– Commodity Trading
– Biotechnology
– Animal feed (pet food and biomaterials)
Biofuels
– Ethanol (derived from food crops and biomass)
– Biodiesel (multiple feedstocks)
– Clean technologies (commercialization of waste streams and by-products)
HEALTH
Slide 10 2016 Seminar Series - Nov 17 2016
Precision Agriculture: we are talking about?
Tailoring soil & crop management to match conditions at every location in a field from year to year – on a whole farm basis
“Size” of location can vary – e.g. 50cmc, 1ha, 10ha
Location is geographically referenced using GPS
Managing Spatial variability
Slide 11 2016 Seminar Series - Nov 17 2016
In terms of our Buzz words/phrases?
Internet of Things
Drone Technology (robotics)
Big Data
eLandscape
Slide 12 2016 Seminar Series - Nov 17 2016
Internet of Things
IoT = Internet of Things - a network of physical objects that contain embedded technology to communicate, sense &/or interact with their internal states or the external environment + the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction
Leads to “Big Data” – i.e. lots of it
Slide 14 2016 Seminar Series - Nov 17 2016
Wireless Sensor Network (WSN) Mesh typology, flexible, self configuring & healing (fault tolerant) Robust and low maintenance Multiple sensors 6+ Multiple communication protocols • Point to point, star, mesh. • >12 radio interfaces (i.e. Wi-Fi, 3G, LoRA, ZigBee)
Nodes solar powered + 24hrs backup Wi-Fi connected to Eduroam
GRAND TOTAL in the network = 60 nodes, 4 Meshliums, 8 cameras
All OK Problem develops Self healing
Nodes
Meshlium (router for communication)
Slide 15 2016 Seminar Series - Nov 17 2016
Libelium Nodes and Sensors
Smart Agriculture
Smart Water
Smart Environment
Smart Security
Slide 16 2016 Seminar Series - Nov 17 2016
Types of Sensors Installed
Libelium Waspmote Node Model
Sensors possible
Smart Environment Carbon Monoxide (CO), Carbon Dioxide (CO2), Oxygen (O2), Methane (CH4), Hydrogen (H2), Ammonia (NH3), Hydrogen Sulfide (H2S), Nitrogen Dioxide (NO2), Ozone (O3), Hydrocarbons (VOC), Isobutane, Ethanol, Toluene, Temperature, Humidity, Pressure atmospheric, dust particles, Luminosity.
Smart Agriculture Soil moisture, Soil temperature, Leaf wetness, Solar radiation, Atmospheric pressure, Stem diameter, Anemometer, Wind vane, Pluviometer, Ambient temperature, Humidity
Smart Water Temperature, pH, dissolved oxygen, oxidation-reduction potential, conductivity (salinity), turbidity, dissolved ions (Calcium (Ca2+), Fluoride (F-), Fluoroborate (BF4
-), Nitrate (NO3-), Bromide (Br-), Chloride (Cl-), Cupric
(Cu2+), Iodide (I-), Silver (Ag+)
Smart Security Water presence, Liquid level, Liquid flow, Temperature, Humidity, Luminosity
Slide 18 2016 Seminar Series - Nov 17 2016
Technology in place on Campus ARSL
Weather Station atop SAFS
Smart Cities Node on Campus
Multiple sensors
Smart Ag Node
Slide 19 2016 Seminar Series - Nov 17 2016
Agriculture Node Build Modular Components
Finished Ag. Sensor Node Electronic Components
Instrumentation & Materials
Slide 20 2016 Seminar Series - Nov 17 2016
100m x100m mesh
Support Structure for in Paddock Deployment Support Post & Cable Harness
Slide 23 2016 Seminar Series - Nov 17 2016
Wireless Self-Powered Camera
Navas 2016
• WI-FI & 3G connectivity
• Self powered
• Night vision capability (IR Leds)
• Motion detection
• Equine birthing
Slide 24 2016 Seminar Series - Nov 17 2016
Smart Campus + TEL TEL PROJECT Smart Campus Initiative (IoT)
Slide 26 2016 Seminar Series - Nov 17 2016
Waste Water PBL Lake Galletly, Mac’s Pond, Lake Lenore are all part of the Waste Water Management system at UQGatton Campus
Slide 27 2016 Seminar Series - Nov 17 2016
So What?
Ok – we have large amounts of biophysical data coming in – what else do we need – and for what?
• Want to use it for lots of things
Pasture monitoring & management
Animal monitoring & management
Crop monitoring & management
Education
More data ! - eg Aerial data
Drones
Slide 28 2016 Seminar Series - Nov 17 2016
Back to the Future - New Technologies in Ag
Remote Sensing (since early 1970s) – Gathering data at a distance across large areas for spatial variability
monitoring
– Eg Satellite or Airborne
Chequered history in Ag with 2 main issues 1. Data
• Cost of acquisition & processing • Revisit Frequency • Resolution • Requires cloud/haze free environment • Computing/processing grunt available
2. Lack of skills available in the Agricultural sector
Slide 29 2016 Seminar Series - Nov 17 2016
Industry - Last 5 years Data – Satellite data can be obtained free for whole world through NASA and
other Government databases
– Still has issues of resolution and revisit frequency for agricultural purposes
Exponential growth in the miniaturisation of electronic equipment
• Driven growth of small drones – multirotor and fixed wing
Slide 30 2016 Seminar Series - Nov 17 2016
Drones
Reason for use – Cheap platform to carry high res sensors
– Collect data on spatial variability (SV) Optimising Production Efficiency & Quality
Minimising Risk & Environmental Impact
= SMART FOOD PRODUCTION
= SMART ENVIRONMENTAL MANAGEMENT
= SMART SKILLS DEVELOPMENT Multiple skills and fun!
Drones at UQ
– 2016 UQ’s fleet consists of 5 DJI Phantoms + 4 bespoke Quads + 3 bespoke Hexicopters + 10 MiniAg drones (Ekka)
10 mins to learn to fly ** Vegetables Australia Magazine Article March/April 2015 http://www.ausveg.com.au/publications/VA/VA-MarApr2015.pdf
SV at ground level
SV from the Air
Slide 31 2016 Seminar Series - Nov 17 2016
Navas, 2015
UQGatton Drones
Drone Design Projects 2013-2016 TestDrone, BugDrone, NetDrone, WeedDrone, WildDrone, WhaleDrone, RFIDDrone, Mini-AgDrones with NoIR camera
2013
2014/15
2014
2015
2015/2016
2015/16
2013-2016
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Design & Build = Active Learning
Students from a range of degrees – BSc, BEng, BAgSci, BAgriBus
– Design, build and use a small to medium drone
Learn general design & build principles including testing
Learn to fly
Undertake project
Write Report – develop Recipe/Poster/Paper
Slide 34 2016 Seminar Series - Nov 17 2016
UQGatton Farm from a drone
Paddocks &
Maize Visual
Infrared
Pivot irrigated Lucerne Visual
X X
X
Infrared
*
X
X
X
*
Slide 39 2016 Seminar Series - Nov 17 2016
Robotics
AgBot – QUT
Harvesting
Dairy
Other
Slide 40 2016 Seminar Series - Nov 17 2016
Sensors – What are they recording?
Why is Grass green, or a Tomato red?
Tomatoes are red because when ripe, they contain a carotenoid known as "Lycopene"
Lycopene is a bright red carotenoid pigment which absorbs most of the visible light spectrum, and being red in colour, Lycopene reflects mainly red back to the viewer, thus a ripe tomato appears to be Red
Grass???
Slide 41 2016 Seminar Series - Nov 17 2016
Spectral Reflectance characteristics
Use ENVI software to look at the spectral properties of the ground as recorded
Spectral reflectance characteristics due to:
• Pigmentation • Moisture content • Cellular structure • Mineral & moisture content of soils • Sedimentation levels in water
Raspberry Pi NOIR Sensor on MiniAg Drone
Slide 42 2016 Seminar Series - Nov 17 2016
Multispectral Camera
Based on Raspberry Pi & 4 NoIR multiplexed cameras.
4 selectable wavelength bands (research quality filters)
Slide 44 2016 Seminar Series - Nov 17 2016
Addressing Food Insecurity issues?
Optimising Production Efficiency (IoT and NetDrone)
Optimising Quality (IoT and MiniAg Drone)
Minimising Risk (IoT and WeedDrone)
Minimising Environmental Impact (IoT and BugDrone)
Education (IoT + Drones = Active Learning)
Slide 45 2016 Seminar Series - Nov 17 2016
Big Data
Many definitions:
– Big data is new and “gi-normous” and scary – very, very scary.
– Big data is just another name for the same old data marketers have always used, and it’s not all that big, and it’s something we should be embracing, not fearing.
– Big data is as powerful as a tsunami, but it’s a deluge that can be controlled - in a positive way, to provide business insights and value.
Big data is a collection of data from traditional and digital sources inside and outside the organisationthat represents a source for ongoing discovery and analysis.
Slide 46 2016 Seminar Series - Nov 17 2016
Key Issues for Big data Big Data success is not about implementing one piece of technology (eg Hadoop)
– Requires putting together an assembly line of technologies, people & processes
You need to capture data, store data, clean data, query data, analyze data, visualize data. – Some of this will be done by products, and some of it will be done by
humans. Everything needs to be integrated seamlessly
Slide 49 2016 Seminar Series - Nov 17 2016
‘E’ Agribusiness Supply Chains
Supply Chain Management - originally envisaged as ‘the elimination of barriers between trading partners’
Slide 50 2016 Seminar Series - Nov 17 2016
‘E’ Supply Chains
Companies with a network of suppliers, partners, and customers connected electronically
Because?
– Need a fast, efficient way to do business, disseminate information and enable two-way communications
Involve
– the complete integration of internal ERP & other business systems
– Collaboration with internal and external supply partners
Slide 51 2016 Seminar Series - Nov 17 2016
‘E’Supply Chains & Food Security/Insecurity?
Logistics and Delivery
Food Tracking & Traceability - different but same concepts
All about ‘E’ connectivity and information flow
EReadiness: - the extent to which a country’s business environment is conducive to Internet-based commercial opportunities • Connectivity • Business Environment • Ecommerce & Consumer adoption • Legal & Regulatory Environment • Supporting e-Services • Social & Cultural Infrastructure
Slide 52 2016 Seminar Series - Nov 17 2016
Food Tracking & Traceability
We are what we eat!!!
Coffee
Slide 53 2016 Seminar Series - Nov 17 2016
Food Tracking/Traceability
We Are What We Eat
Traceability: The ability to trace and follow a food, feed, food producing animal or substance intended to be, or expected to be, incorporated into a food or feed through all stages of production, processing and distribution
Traceability systems are record-keeping systems that act as a tool for making information available either within an organization or between organizations
Records have to be authentic, reliable, integral (or whole), useful (and useable)
Product Traceability Systems - Recall
Slide 54 2016 Seminar Series - Nov 17 2016
Two Important Traceability Systems
The Barcode system
The RFID System
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Logistics
Distribution of Food – Specialised Services – Traceability affects supply chain efficiency, product safety and security,
managing deep tier risks, on-time delivery performance, troubleshooting customer issues, controlling costs, and regulatory compliance
USA
Europe - Europool
Slide 56 2016 Seminar Series - Nov 17 2016
Global Food Security & ‘E’ Techs?
Food Security Analysis Data Visualisation
Slide 57 2016 Seminar Series - Nov 17 2016
Food Security Analysis
Decision makers at country, regional and global levels need reliable and timely information – on the incidence and causes of food insecurity, malnutrition and vulnerability
– for improved policy and program formulation aimed at reducing poverty and hunger
Problem: – A lack of common definitions for classifying various food security situations in terms
of varying severity and implications for action
– Problematic for several reasons: • What data has been used
• The way a situation is classified determines not only the type of response, but also the source of funding, scale, planning timeframe, and organizational roles of different stakeholders.
• Without commonly accepted standards for classifying the nature and severity of food security situations, the design and targeting of interventions can be open to personal, government, agency, and donor biases.
Slide 58 2016 Seminar Series - Nov 17 2016
Analysis Frameworks
There are 3 examples of Analysis Frameworks that have been developed over time and show this lack of commonality: – VAM – Vulnerability Analysis Mapping – from the World Food Programme (WFP) –
the largest humanitarian agency fighting hunger worldwide
– FIVIMS – Food Insecurity and Vulnerability Mapping – from FAO - the Food and Agriculture Organization of the United Nations (2015 - No Longer Operational)
– FSF - Food Security Framework – from USAID - United States Agency for International Development
Slide 59 2016 Seminar Series - Nov 17 2016
The World Food Programme (WFP) & VAM
WFP's food security analysis work is commonly known as VAM (Vulnerability Analysis and Mapping)
VAM is based around knowing the answers to the following questions: – Who is food insecure or vulnerable? – How many are they? – Where do they live? – Why are they food insecure or vulnerable? – How is the situation likely to evolve and what are the risks threatening them? – What should be done to save their lives and livelihoods?
And helps to: – Identify the most appropriate type and scale of intervention, whether food distributions, school feeding, etc – Identify support to re-establish livelihoods or more innovative interventions such as cash or voucher programmes; – Identify the most food insecure people to ensure the most effective targeting; – Ensure the most efficient use of humanitarian resources, by allocating funding according to needs
Slide 60 2016 Seminar Series - Nov 17 2016
FAO & FIVIMS
The FAO’s FIVIMS Initiative (Food Insecurity and Vulnerability Mapping System) promoted cross-sectoral analysis. It aimed at: – Raising awareness about food security issues – Improving the quality of food security related data and analysis – Facilitating the integration of complimentary information – Promoting a better understanding of User’s needs and a better use of information – Improving access to information through networking and sharing
The FIVIMS conceptual framework is a cross-sectoral food security analysis helps strengthen the understanding of why people are food insecure, malnourished or hungry
There are four key dimensions associated with the analysis: – Food availability – Food Access – Supply stability – Resource Utilisation
Slide 62 2016 Seminar Series - Nov 17 2016
USAID
The USAID food security framework highlights the three dimensions of Food Availability, Food Access, and Resource Utilization and the nature of their relationship to one another, and what determines these relationships
– Food availability is a combination of domestic food stocks, commercial food imports,
food aid, and domestic food production, & the underlying determinants of each of these factors
– Food access is influenced by the aggregate availability of food through availabilities impact on supplies in the market and, therefore, on market prices
– Resource Utilisation - food access also is a function of the physical environment, social environment and policy environment which determine how effectively households are able to utilize their resources to meet their food security objectives. Drastic changes in these conditions, such as during periods of drought or social conflict, may seriously disrupt production strategies and threaten the food access of affected households.
Slide 63 2016 Seminar Series - Nov 17 2016
Food Security Monitoring
Monitoring - the systematic collection and analysis of information to provide information for decision-making to answer the following questions:
– How much food is the world producing? – What is happening to world food prices? – What is the impact of El Niño and La Niña weather events on food production – How is the monsoon progressing in East Asia? – Will there be a drought in southern Africa this year? – What is the impact of floods and other weather hazards on food production? – What are the food security implications of civil war, economic crises or other man-made
disasters? – Which countries are the most food-insecure? – Where are food interventions most needed? – Where are cereal surpluses available for local purchases or triangular transactions?
Slide 64 2016 Seminar Series - Nov 17 2016
Food Security Monitoring
A system or series of systems is needed that can – Monitor food supply and demand in all countries of the world on a continuous basis
– Compile and analyse information on global production, stocks, trade and food aid
– Monitor export prices and developments on main grain exchanges
– Provide up-to-date reports and information to the international community through regular publications, special reports, e-mail and its web pages on the Internet
– Answer specific requests for information, from governments, NGOs, research institutions and individuals
– Develop new approaches and technologies for early warning and make these available to national and regional early warning systems
– Cultivate and maintain a commitment to global food information-sharing between governments, NGOs, other UN agencies, research institutions, the international press and private individuals
Slide 65 2016 Seminar Series - Nov 17 2016
GIEWS
By far the most well known and well developed system is GIEWS -FAO’s Global Information and Early Warning System on Food and
Agriculture
– Created in 1975, the FAO’s Global Information and Early Warning System on Food and
Agriculture (GIEWS) has been providing policymakers and policy-analysts with the most up-to-date and accurate information available on all aspects of food supply and demand
• Provides regular bulletins on food crop production and markets at the global level and situation reports on a regional and country-by-country basis and warns of imminent food crises, so that timely interventions can be planned and suffering avoided
Slide 66 2016 Seminar Series - Nov 17 2016
GIEWS
The Service is responsible for planning and backstopping FAO-supported Regional and National Early Warning and Food Information Systems
In case of impeding food emergencies, the System dispatches rapid Crop and Food Supply Assessment Missions (CFSAM) to the afflicted regions, often jointly with the World Food Programme (WFP).
Slide 67 2016 Seminar Series - Nov 17 2016
Food Security Mapping
Mapping - Knowing the spatial distribution of vulnerability to
food insecurity as well as understanding the determining factors is a prerequisite in the situation analysis needed for designing and planning responses to food insecurity
– Need to create maps that help governments, donors and
development agencies to understand the underlying causes of poverty
• Dynamic vulnerability in food insecurity maps