food security and safety: opportunities within the...

© 2009 IBM Corporation

IBM Research

Food Security and Safety: Opportunities within the Advanced Technology Sector of IndustryGovernment-University-Industry Research Roundtable Meeting, February 4, 2009

Mary E. Helander, Ph.D.IBM T.J. Watson Research CenterBusiness Analytics and Mathematical Science DepartmentYorktown Heights, NY

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Food Security and Safety: Opportunities within the Advanced Technology Sector of Industry

Abstract

§ Are there some specific opportunities within the Advanced

Technology sector of Industry that can speed development of

solutions in Food Safety and Security? This is the question to be

addressed in this session.

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Specific Opportunities

1. Supply chain management

2. Advanced analytics

3. IT infrastructure

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Advanced supply chains allow the ability to track and trace entities through a multi-enterprise supply chain. Supply chains for food present unique challenges

| Complex networks of trading partners, including global sourcing

| Heterogeneous technological capabilities

| Non-homogeneous data

| Non-digital, incomplete, or unreliable data

| Disparate data sources

| Benefits not gained by trading partners who incur costs

| Difficult governance

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DISTRIBUTION

§ Retailer Metro AG - RFID system for tracking consumer products from production through transport & warehousing to

sale and customer service

GOVERNMENT

§ UK Government Department for the Environment, Food & Rural Affairs – building Systems for Animal Movement and

Traceability using RFID and GPS

§ Japan - Waste Disposal Traceability Pilot

§ Government of Thailand - RFID pilot on Shrimp Traceability

AUTOMOTIVE

§ Honda - Infrastructure for Data/Process Integration including Traceability

§ Japan - Automotive Parts Traceability prototype

AGRICULTURE

§ Maple Leaf Foods - DNA traceability pilot for pork

§ Major beef farm & processor in US Midwest - RFID system for farm to fork traceability to meet new state regulations

and create a premium brand positioning

PHARMACEUTICAL

§ Japanese Ministry of Internal Affairs and Communications - Pharmaceutical Traceability

Learning from other industries can help speed solutions for food safety and security. These are a few examples of traceability projects for public and private sector clients across many different industries.

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Gaining full compliance to a voluntary end-to–end traceability system depends on identifying the benefits for each participant in the Supply Chain

Technological Infrastructure & Common Business Processes

Sector/Commodity Specific Business Processes

Food Continuum/Supply ChainProducer/Grower

• Increased farm efficiency

• Individual animal/product value-added information from processor

• Increased yields –business analytics from feed, pesticides, processor

• Increased and secure access to global markets

• Risk mitigation and reduced liability

Processor

• Increased service offerings to clients

• More detailed understanding of input and throughput by client

• Increased quality control


Distributor

• Increased productivity

• Improved inventory

• Improved shipping/ receiving accuracy

• Demand visibility and forecasting

• Decreased diversion expenses


Retailer

• Increased productivity/supply chain optimization




• Refined client behaviour information

• More efficient marketing


Customer

• Increased confidence in food supply

• Lower prices

• Greater availability of products and services

Secure Transportation/Secure Trade Lanes

Government

• Improved public safety

• Increased competitiveness

• International trade

• Risk mitigation

• Reduced compensation

Infrastructure• Interoperable

• Globally compliant

• Flexible/ scaleable

Demand/Information Flow

Farm Input/Supplier

• Increased productivity/supply chain optimization




• Refined client behaviour information

• More efficient marketing


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Various technologies exist, e.g. sensors and actuators for data capture. Enabling efficient and effective food safety and security solutions is still a logistical challenge

FARMFARM Slaughterhouse/Processor

Slaughterhouse/Processor

MarketsMarkets

Local Database

Local Database

Local Database

Central Repository Database

Qu

ery

Animal Testing

Animal Testing

Local Database

Query Query

Local Database

FARMFARM Slaughterhouse/Processor

Slaughterhouse/Processor

MarketsMarkets

Local Database

Local Database

Local Database

Central Repository Database

Qu

ery

Animal Testing

Animal Testing

Local Database

Animal Testing

Animal Testing

Local Database

Query Query

Local Database

serial comms

Bar Code reader

serial comms

Internet IP

J2SE

Bar Code tag

<Animal Location Record><Land Parcel Bar Code/><Gov Gateway Credentials/><Ear Tag Bar Code/><Date and Time/>

</Animal Location>

<Animal Location Record><Land Parcel Bar Code/><Land Parcel Geometry/><Gov Gateway Credentials/><Customer ID/><Ear Tag Bar Code/><Animal ID/><Date and Time/>

</Animal Location>

Livestock Register Services

Enterprise Service Bus

Corporate Repositories

internet

Field 1

Field 2

Field 3

Personalised Barcode Pamphlet serial comms

Bar Code reader

serial comms

Internet IP

J2SE

Bar Code tag

<Animal Location Record><Land Parcel Bar Code/><Gov Gateway Credentials/><Ear Tag Bar Code/><Date and Time/>

</Animal Location>

<Animal Location Record><Land Parcel Bar Code/><Land Parcel Geometry/><Gov Gateway Credentials/><Customer ID/><Ear Tag Bar Code/><Animal ID/><Date and Time/>

</Animal Location>




internet

Field 1

Field 2

Field 3

Personalised Barcode Pamphlet

Bluetooth

GPS unit

RFID reader

Bluetooth

GPRS

J2ME

RFID tag

<Animal Location Record><Spatial Position/><SIM Card ID/><RFID Tag ID/><Date and Time/>

</Animal Location>

<Animal Location Record><Spatial Position/><Land Parcel Geometry/><SIM Card ID/><Customer ID/><RFID Tag ID/><Animal ID/><Date and Time/>

</Animal Location>




internet

Bluetooth

GPS unit

RFID reader

Bluetooth

GPRS

J2ME

RFID tag

<Animal Location Record><Spatial Position/><SIM Card ID/><RFID Tag ID/><Date and Time/>

</Animal Location>

<Animal Location Record><Spatial Position/><Land Parcel Geometry/><SIM Card ID/><Customer ID/><RFID Tag ID/><Animal ID/><Date and Time/>

</Animal Location>




internet Stroke Reco ServerStroke Reco Server

Animal verification via RFID taggingBarcode based near real time animal movement data capture

GPS based real time animal movement data capture Digital Pens and Workplace Forms used in traditionally low tech environments

| 10 © Copyright IBM Corporation 2009

Data security maintained via encryption, restricted password access, etc…

Secure, standards-based queries enabled

A track and trace system that supports food safety and security must capture, structure and integrate data on product a) movements, b) attribute changes, and c)processing activities from across and within the supply chain

Example: Beef - Each company maintains its own product information and record of transactions, making that information available on a permission basis to stakeholders

Rapid communication of essential data facilitated through open-standard software

and adoption of industry ID standards

Antibiotics

Logistics Logistics

Fertilizers Packaging Ingredients

Logistics

Ingredients

Logistics

Data Data Data Data DataData

Virtual Traceability System

Logistics Logistics Logistics LogisticsLogistics

Grocery Store/

RestaurantCorn Farmer

Cattle Rancher

Distribution Center

Beef Processor

CP Manufacturer

Transaction & Historical Data

FirewallFirewallFirewallFirewall

FirewallFirewall

Fir

ew

all

Track and trace products and risks within the four walls to isolate and prevent issues

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Opportunities for data analytic technologies in food safety and security solutions

§ Data Mining– The process of extracting hidden patterns from data

– Increasingly important tool as the volume of data increases

§ Predictive Modeling– The process of trying to best predict the probability of an

outcome

§ Risk Analysis– The process of identifying and assessing factors that

jeopardize the success of a goal

§ Statistical Analysis and Forecasting– The mathematical science of collection, analysis,

interpretation, explanation, and presentation of data, and estimating unknown quantities

Antibiotics

Logistics Logistics


Logistics

Ingredients

Logistics




Grocery Store/


Cattle Rancher

Distribution Center

Beef Processor

CP Manufacturer



FirewallFirewall

Fir

ew

all


Antibiotics

Logistics Logistics


Logistics

Ingredients

Logistics




Grocery Store/


Cattle Rancher

Distribution Center

Beef Processor

CP Manufacturer



FirewallFirewall

Fir

ew

all


What conditions existed prior to a food safety event?

Based on identified patterns, predict the probability of a future food safety event

Make decisions on risk mitigation. For example, product recall prior to a food safety event

Support impact analysis by forecasting demand under different hazard scenarios

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Risk models appear to be particularly relevant for food safety and security solutions

§ Statistical and machine learning models, used to discover key risk indicators and characterize likelihood and impact of risks based on historical data;

§ Simulation models, which are (usually) data-driven representations of a system facilitated by sampling from specified probability distributions.

§ Stochastic optimization models, where at least one of the variables involves uncertainty, and is assumed to follow a particular probability distribution

Ref: Ray, Apte, McAuliffe, Deleris and Cope, Harnessing Uncertainty: The Future of Risk Analytics, IBM Research Report, 2008

A layered view of the enterprise that maps key resources supporting business processes, and the causes of failures affecting these resources

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Why “advanced data analytics” is a technology to consider in food safety and security solutions?

§ Methods deal with large volumes of dataand address computational complexity

§ Unstructured data may be leveraged for improving predictive accuracy and insights

§ Approaches consider missing data and uncertainty

§ Even more powerful when combined with visualization tools

§ Advanced data analytics are the key for moving food safety and security from reactive to preventative

Stack graph Line graph Bar chart Scatterplot

US Map World map Block histogram Bubble chart

Pie chart Treemap (2 types) Stack graph for categories Network diagram

Stack graph Line graph Bar chart Scatterplot

US Map World map Block histogram Bubble chart

Pie chart Treemap (2 types) Stack graph for categories Network diagram

http://manyeyes.alphaworks.ibm.com/manyeyes/

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In system design for safety, the highest priorities are assigned to hazard prevention. Advanced data analytics help to move in this direction.

TimeHazard event

occurs

x

DamageMinimization

DamageMinimization

A hazard event has occurred. Minimize the damage.

HazardControlHazardControl

A hazard event has occurred. Mitigate the effects.

HazardReduction

HazardReduction

Minimize the probability of future hazard events occurring.

HazardElimination

HazardElimination

Complete elimination of the possibility for future hazard events.

* Reference: N. Leveson's adaption in Safeware: System Safety and Computers, Addison-Wesley, 1995 of the safety precedence described by W. Hammer, Handbook of System and Product Safety. Prentice-Hall, Inc. Englewood Cliffs, NJ, 1972.

PR

IOR

ITY

Traceability enables improved reaction given a food safety hazard has occurred

Advanced data analytic methods take large volumes of data from various sources, including from traceability solutions, to enable prediction and avoidance

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| 17 © Copyright IBM Corporation 2009

Since the constituent database systems often must remain autonomous, a federated database system is an alternative to the (sometimes daunting) task of merging together several disparate databases

Antibiotics

Logistics Logistics


Logistics

Ingredients

Logistics



Grocery Store/

Restaurant

Corn FarmerCattle

RancherDistribution

CenterBeef

Processor

CP Manufacturer

Federated data base

Data to Smart Decisions - 18©2009 IBM Corporation

2005 2006 2007 2008 2009 2010 20110

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Ex

ab

yte

s

DVD,RFID,

Digital TV,MP3 players,

Digital cameras,Camera phones, VoIP,

Medical imaging, Laptops,Datacenter applications, Games,

Satellite images, GPS, ATMs, Scanners,Sensors, Digital radio, DLP theaters, Telematics,

Peer-to-peer, Email, Instant messaging, Videoconferencing,CAD/CAM, Toys, Industrial machines, Security systems, Appliances

TenfoldGrowth in

Five Years!

TenfoldGrowth in

Five Years!

PhysicalRDFdocuments

2+ billion

RDF triples

Over 10,000ontologies

10M documents401M triples

Real-worldRDF Applications

12/07 04/08

Data arises from many sources (instrumentation, automation, on-line communities). Managing and preparing the data for use is a necessary first step in data-driven decision making.

Gather Data

Data cleansingSearchingFeature extraction

Semantic linking and extractionStream processingCrowd computing

Data to Smart Decisions

Define ProblemAct, Monitor,

Learn

DecideAnalyzeGather data

The number of semantically tagged documents and data sets is growing dramatically, improving data gathering capabilities.

The volume of digital data is exploding§80% of new data growth is unstructured§Data and metadata quality varies§Better approaches to finding relevant data are critical

Cloud - 19©2009 IBM Corporation

Flexible pricingFlexible pricing

Rapid provisioningRapid provisioning

Cloud Computing is a model of shared network-delivered services, both public and private, in which the user sees only the service, and need not worry about the implementation or infrastructure

InfrastructureServices

PlatformServices

ApplicationServices

BusinessServices

PeopleServices

Built on radically scalable, manageable, virtualized IT resources

Built on radically scalable, manageable, virtualized IT resources

Service layers separated by clean APIs, enabling

composition.

Service layers separated by clean APIs, enabling

composition.

Important roles for both public and private

clouds.

Important roles for both public and private

clouds.

Consumable web-delivered services

requiring no installation, minimal setup

Consumable web-delivered services

requiring no installation, minimal setup

Elastic scalingElastic scaling

Advanced virtualization

Advanced virtualization

Standard Internet technologies

Standard Internet technologies

Cloud

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IBM Research


Other recommendations to speed development of food safety and security solutions

1. Form real G-U-I teams to study the problem, identify gaps, and prioritize solution development approacheso Combine domain experts with technology, commercial and regulation expertise

o Take a ”system” view that recognizes multi-perspective, multi-objective aspects

2. Find ways to propose / contribute toward the economic stimulus packageso Mainly, financial stabilization, but includes spending in 2 other key areas

3. Take advantage of existing experiences w/ G-U-I relationships, e.g.o Joint research programs

o Programs for interns and summer students

o Research mentorship

o Workshops, various outreach

4. Learn from other industrieso Retail, Government, Automotive, Agriculture, Pharmaceutical, …

Creating Innovative Solutions With IBM Research © 2009 IBM Corporation21

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Example: Value of IBM’s FOAK Program

§ Links Research strategic initiatives to real client challenges

Validate market requirements

Test market readiness

§ Accelerate delivery of new technologies to the market

Enhance core technologies

Create new offerings

Enable On Demand Innovation Services (ODIS) engagements

§ Provide headlights into emerging market opportunitiesUncover new markets and growth opportunities

§ Gain valuable experience and thought leadershipSkills and knowledge transfer

§ Facilitate solution sales

Proof points for reuse

§ Create mindshareReferences and differentiation

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Economic Stimulus:Government Spending Prioritized in Three Key Areas

New energy sourcesSustainabilityIndustry change Research

Intelligent transportationShared servicesCustoms, ports, borders

InfrastructureSmart gride-healthSchools modernizationBroadband

Cross sector stimulus

Loan managementRisk assessment and management

Financial stabilization and reform

Regulatory systemsTroubled assetsSocial safety net systems

Focus

Government stimulus

Program

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