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SYSTEMS OF IOT SYSTEMS FOR
SMART FOOD AND FARMING
Cor Verdouw, Jeroen van Grondelle, Robbert Robbemond, Sjaak Wolfert
Wageningen University & Research
AgEng2018, July 10th 2018, Wageningen, The Netherlands
2
MEAT
ARABLE
VEGETABLES
FRUITS
DAIRY
A SYSTEM OF 19 USE CASE SYSTEMS
IOF2020 > SUM OF THE USE CASES
Synergies across use cases crucial for large-scale take-up
3
OUTLINE OF THE PRESENTATION
4
Systems of Systems approach
Analysis Use Case Architectures
Main Commonalities
Recommended synergy actions
SYSTEM OF SYSTEMS
arrangement of systems that results when independent
and useful systems are integrated into a larger system
that delivers unique capabilities
(Tekinerdogan, 2017)
5
Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products
are transforming competition. Harvard Business Review, 92(11), 64-88.
CRITERIA SYSTEM OF SYSTEMS (MAIER 1998)
• Operational Independence of Elements
• Managerial Independence of Elements
• Evolutionary Development
• Emergent Behavior
• Geographical Distribution of Elements
6
Heterogeneity
Not prescribing
particular tools or
technologies!
Convergence through Synergy and Reuse
In all life cycle phases
OUR SYSTEM OF SYSTEMS APROACH
OUTLINE OF THE PRESENTATION
8
Systems of Systems approach
Analysis Use Case Architectures
Main Commonalities
Recommended synergy actions
9
ANALYSIS APPROACH
• Tag at the level of use cases first
• Logical (functions and data) and
technical dimension
• Validation by the use case owners
10
Measures: Humidity
Predicts: Crop Growth
Controls: Water supply
(to influence: Yield)
Lora Connectivity
Deployed near Animals
IOT FUNCTIONS
Measure
Ingest
Derive
Predict
11
Monitor
Control
Plan
Report
Alert
DATA
USE OF THE DIFFERENT IOT FUNCTIONS
12
CONTROL CYCLES OF THE USE CASES
DATA MODEL ANALYSIS: A LOT OF DIVERSITY
14
MAIN DATA CATEGORIES
15
PRELIMINARY DATA MODEL ANALYSIS
• We see common underlying information modeling questions
• How to model time and location of sensor measurements
• Time dimension
• Continuous time series from static sensors
• Measurements from incidentally/nomadic deployed sensors
• Measurements from machine operation
• Location, measurements of different granularity
• Crop growth/m2, rain measurements for complete field
• Crop growth measurement after each weeding, rain every 15 minutes
• Comparing/correlating data from different resolution granularity
• Critical for sharing and reusing data for new use cases
16
CONNECTIVITY MODELS
13 of the UCs use some
form of LPWAN or LR-
WPAN
Existing tech such as
Wifi, Bluetooth, Ethernet
and Serial Bus remain
very relevant
NB-IoT not used
DEVICE ARCHITECTURES
Majority uses
mature, of-the-shelf
sensors
In line with
expected technical
readiness level of
project
LOCATION
Mainly GPS for outdoor
positioning
Opportunities for new
localization approaches
Lora/Sigfox based
Beacons
Large diversity!
Quite a few platforms
undecided (at time of
drafting D3.2)
Strong base in FIWARE
stack
IOT PLATFORMS
OUTLINE OF THE PRESENTATION
21
Systems of Systems approach
Analysis Use Case Architectures
Main Commonalities
Recommended synergy actions
MAIN LOGICAL COMMONALITIES
• Animal Characteristics
• Health, Fertility, Weight, Feed Intake,
Movements, Genetics, …
• Crop Characteristics
• Incl. Growth, Water Stress, Fertilizer
Need, Pests, ....
• Outdoor Conditions
(weather)
• Incl. Temperature, Solar Radiation,
Rainfall, Wind, …
• Soil Characteristics
• Incl. Moisture, Temp, EC, Nutrients, …
22
• Indoor/Storage/Trans-
portation Conditions
• Incl. Temp, Humidity, Noise,
CO2, …
• Location
• Incl. Position of Animals, Crops,
Trees, Equipment, RTIs, ....
• Food Product
• Incl. Grain Humidity,
Chemical/Microbiological Quality
Dairy Products, Wine
Temperature, Soya Protein
Levels, Carcass Parameters, ....
MAIN COMMONALITIES TECH PERSPECTIVE
• Connectivity
• Low Power Long Range
Connectivity (Lora/Sigfox)
• Short range (LR-WPANs
• Localization
• GPS
• Lora/Sigfox localization
• Beacons
• Device architecture
• autonomous
deployment/solar/battery
23
• IoT data management
• FIWARE Context Broker
• FIWARE IoT Agent
• EPCIS
• 365FarmNet
• Supporting IoT
capabilities
• Device management
• Security
RECOMMENDED NEXT STEPS
24
Catalogue &
Market Place
Task Forces &
Guidelines
Identify Gaps
for Open Call
Develop
Reusable
Components
Reference Data
Models
Joint business models/
exploitation of solutions
MANY THANKS FOR
YOUR ATTENTION!
Cor Verdouw, Jeroen van Grondelle, Robbert Robbemond, Sjaak Wolfert

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Systems of IoT Systems for Smart Food and Farming

  • 1. SYSTEMS OF IOT SYSTEMS FOR SMART FOOD AND FARMING Cor Verdouw, Jeroen van Grondelle, Robbert Robbemond, Sjaak Wolfert Wageningen University & Research AgEng2018, July 10th 2018, Wageningen, The Netherlands
  • 3. IOF2020 > SUM OF THE USE CASES Synergies across use cases crucial for large-scale take-up 3
  • 4. OUTLINE OF THE PRESENTATION 4 Systems of Systems approach Analysis Use Case Architectures Main Commonalities Recommended synergy actions
  • 5. SYSTEM OF SYSTEMS arrangement of systems that results when independent and useful systems are integrated into a larger system that delivers unique capabilities (Tekinerdogan, 2017) 5 Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
  • 6. CRITERIA SYSTEM OF SYSTEMS (MAIER 1998) • Operational Independence of Elements • Managerial Independence of Elements • Evolutionary Development • Emergent Behavior • Geographical Distribution of Elements 6 Heterogeneity Not prescribing particular tools or technologies! Convergence through Synergy and Reuse In all life cycle phases
  • 7. OUR SYSTEM OF SYSTEMS APROACH
  • 8. OUTLINE OF THE PRESENTATION 8 Systems of Systems approach Analysis Use Case Architectures Main Commonalities Recommended synergy actions
  • 9. 9
  • 10. ANALYSIS APPROACH • Tag at the level of use cases first • Logical (functions and data) and technical dimension • Validation by the use case owners 10 Measures: Humidity Predicts: Crop Growth Controls: Water supply (to influence: Yield) Lora Connectivity Deployed near Animals
  • 12. USE OF THE DIFFERENT IOT FUNCTIONS 12
  • 13. CONTROL CYCLES OF THE USE CASES
  • 14. DATA MODEL ANALYSIS: A LOT OF DIVERSITY 14
  • 16. PRELIMINARY DATA MODEL ANALYSIS • We see common underlying information modeling questions • How to model time and location of sensor measurements • Time dimension • Continuous time series from static sensors • Measurements from incidentally/nomadic deployed sensors • Measurements from machine operation • Location, measurements of different granularity • Crop growth/m2, rain measurements for complete field • Crop growth measurement after each weeding, rain every 15 minutes • Comparing/correlating data from different resolution granularity • Critical for sharing and reusing data for new use cases 16
  • 17. CONNECTIVITY MODELS 13 of the UCs use some form of LPWAN or LR- WPAN Existing tech such as Wifi, Bluetooth, Ethernet and Serial Bus remain very relevant NB-IoT not used
  • 18. DEVICE ARCHITECTURES Majority uses mature, of-the-shelf sensors In line with expected technical readiness level of project
  • 19. LOCATION Mainly GPS for outdoor positioning Opportunities for new localization approaches Lora/Sigfox based Beacons
  • 20. Large diversity! Quite a few platforms undecided (at time of drafting D3.2) Strong base in FIWARE stack IOT PLATFORMS
  • 21. OUTLINE OF THE PRESENTATION 21 Systems of Systems approach Analysis Use Case Architectures Main Commonalities Recommended synergy actions
  • 22. MAIN LOGICAL COMMONALITIES • Animal Characteristics • Health, Fertility, Weight, Feed Intake, Movements, Genetics, … • Crop Characteristics • Incl. Growth, Water Stress, Fertilizer Need, Pests, .... • Outdoor Conditions (weather) • Incl. Temperature, Solar Radiation, Rainfall, Wind, … • Soil Characteristics • Incl. Moisture, Temp, EC, Nutrients, … 22 • Indoor/Storage/Trans- portation Conditions • Incl. Temp, Humidity, Noise, CO2, … • Location • Incl. Position of Animals, Crops, Trees, Equipment, RTIs, .... • Food Product • Incl. Grain Humidity, Chemical/Microbiological Quality Dairy Products, Wine Temperature, Soya Protein Levels, Carcass Parameters, ....
  • 23. MAIN COMMONALITIES TECH PERSPECTIVE • Connectivity • Low Power Long Range Connectivity (Lora/Sigfox) • Short range (LR-WPANs • Localization • GPS • Lora/Sigfox localization • Beacons • Device architecture • autonomous deployment/solar/battery 23 • IoT data management • FIWARE Context Broker • FIWARE IoT Agent • EPCIS • 365FarmNet • Supporting IoT capabilities • Device management • Security
  • 24. RECOMMENDED NEXT STEPS 24 Catalogue & Market Place Task Forces & Guidelines Identify Gaps for Open Call Develop Reusable Components Reference Data Models Joint business models/ exploitation of solutions
  • 25. MANY THANKS FOR YOUR ATTENTION! Cor Verdouw, Jeroen van Grondelle, Robbert Robbemond, Sjaak Wolfert

Editor's Notes

  1. The core of the project lies within 5 trials. These cover 5 sectors (arable, dairy, fruits, vegetables and meat). To showcase each of the trials, the project is organized around 19 use cases.
  2. Information-centric Provides user with up-to-date and historic sensor data for better decision making In architectures: Dashboards, descriptive analytics Task-oriented Decision Support Actively supports users in specific, task oriented decisions using intervention suggestions, i.e. irrigation map, machine settings. User decides. In architectures: Statistical Models, Algorithms, Predictive Analytics Automated Control and/or Planning The system (semi-) autonomously intervenes based on sensor data to reach preset objectives or optimize selected outcome variables Farmer in principle accepts systems interventions, but may override/adjust In architectures: Actuation based on models, prescriptive analytics