Boniface AKUKU, Director Information and Communication Technology, Kenya Agricultural and Livestock Research Organization

1. Kenya Agricultural & Livestock Research Organization
e-Weather/e-Climate Information Services for Sustainable Development
in Africa
Boniface Akuku
Director, ICT
Climate Information Prize Winner, 2016
Chair CODATA – Agricultural Data, Knowledge and Learning Task Group- France
External Cooperation Infopoint Conference- European Commission
27th November, 2018, Brussels, Belgium

2. Why e-climate/e-weather information services- State of Agriculture in Africa is not good
1. Productivity is low and falling
2. Farmers lack critical information on TIMPS
3. Farmers can not make sense of weather data as
currently provided (Farmers are weather watchers)
4. Policy makers lack precise data to enable timely
decision making (e.g. Early warning/alerts provision)
5. Low met network coverage- leading to
inadequate/inaccurate climate/weather data provision
6. Food production is declining
7. Agricultural production environment is hurting
8. Global Competition is a real threat
9. Global markets volatility continues
10. Weak Research-Extension-Farmer Linkage
leading to low adoption & adaption of TIMPs
Almost every drawers has
data/information that
Stakeholders/farmers need
Access to climate/weather data,
information and Knowledge is
problematic,
yet “hidden hunger afflicts 2
billion individuals globally”
(FAO,2013)

3. Location & Number of Active Ground weather station in Kenya

4. Unused climate data and prediction & implications: Kajiado,
Kenya 2017

5. Effects of climate change: The case of Kajiado, Kenya 2017
Africa must invest in capacity building in data science, predictive data analytics and timely reporting to
help realize the impact change this can make to livelihood

6. Disease Crisis
(MLND)
Nothing to Show for Hard Work but Burnt Field
of Maize
Gertrude earns a living harvesting maize on a
small piece of land in rural home, or at least
she used to (May 22 2012 (IPS).

7. The Main Challenges in African Agriculture
70%
2050
30%
40
50%
70%
Population Growth Arable LandWater Consumption

8. Why Agriculture focus in Africa
Critical sector for Africa
Employs 60%+ of population
Feed 1.2B & growing
BUT
Climate change is a challenge
40% food decline
Grow production w/o hurting environment
Global Competition
Volatile Global markets

9. Applications of
ICTs & social
innovations
Availability
of Climate/
weather
information
(Satellites,
RS,
GPS etc)
e-
information
services
provision
Use of
automation
IoT/
Sensors/im
agery/dron
es
The Answer is e-climate/weather information services provision

10. Sustainable development in Africa requires unleashing of
Innovations driven by Technology
Productivity
Quality
Water consumption
Contamination
e-information
services on
weather/climate
& agricultural
research

11. KALRO’S APPROACH:
Digitizing the development of agricultural
value chain in Kenya

12. Objectives
1. Develop, customize and operationalize e-platforms for GAPs, marketing &
weather/climate advisory services
2. Use ICT innovations and compute power to address agricultural production constraints
3. Train potential agricultural value chain stakeholders to effectively and sustainably use the
e-information products and services
4. Improve and enhance access to agricultural information through innovation & ICT/digital
technology
KALRO’s Research Informatics Approach:
Bridging the Gap between Research and Practice using ICT

13. Foliar diseases
Agro-weather Tool
KALRO DIGITAL
PLATFORMS
Kenya Rice Knowledge Bank
Kenya Pollination Information
Network
Kenya Agricultural
Information Network
KALRO e-Mimea Clinic
ASAL K-Hub & mobile
Apps
KALRO APPROACH:
ICT Innovations & Interventions
(Bridging the gap b/n Research &
Practice at farm level

14. 14 Confidential
KALRO ASAL KNOWLEDGE HUB: Supported by EU funded Project

15. KALRO ASAL KNOWLEDGE HUB & MOBILE APPS: EU supported

16. Information Content on mobile apps:
 KALRO varieties and seed catalogue
 Guidelines in acquisition of KALRO
technologies
 Production and management of selected crops
 Disease and pest control
 Record keeping
 Market information
 Economic analysis
 Inbuilt advisory services
 Reporting
 Networking & social media

17. New: USAID Supported 2018
1.Avocado production
2.Banana production
3.Cassava production
4.Fall armyworm (FAW) reporting & mapping in Kenya
5.Garlic production
6.Grey leaf spot (GLS) disease resistant maize varieties
7.Guava production and utilization
8.Maize Lethal Necrosis (MLN) disease control
9.Mahindi-bora Kenya highlands
10. Guideline on production of medicated feed blocks
11. New KALRO cowpea varieties
12. Potato Cyst Nematode (PCN) Control
13. Production of pomegranate and utilization
14. Spider flower production
15. Sugar Cane
16. Aquaculture
17. Goose berry
Mobile App
European Union Supported: 2017
1.Dryland crops
2.Indigenous chicken
3.Range pastures seed production

18. Avocado production
KALRO avocado varieties
Climatic range and soil type
Land preparation and planting
Irrigation, pollination and inter-cropping
Fertilizers, mulching and weeding
Pest and disease management
Bearing and harvesting
Post-harvest handling and fruit management
Economics and market information
Facebook
Contacts details
How to download KALRO farmer mobile application to
your android phone
1. Open google play store on your home page
2. Search KALRO and select farmer mobile app of choice
3. Select install avocado production
4. Wait for a few seconds as the app downloads to your
phone

19. Other Initiatives
• Weekly SMS
From other players
Figure 1: Weekly weather SMS update from KMD & WeFarm
Figure 6: A community member at Wapet displays harvested tomatoes ready for
sale

20. A farmer posted Practical Impact/results
A farmer from Western Kenya
Hasa Omutelema in EMUHAYA
district VIHIGA County
production increased:
Due to application of improved
soil fertility management
information obtained from
KALRO’s digital platforms on
Ecological Organic Agriculture
(EOA)

21. PREDICTIVE DATA ANALYTICS – Power BI or any BDA
• Historical Trends
• Relationships
• Associations
• Predictions
• Patterns, among others

25. Result from the pilot agro-weather Tool in Kenya: Crop Calender

26. Predictive Model of Temperature in Uganda –using web crawling and scrapping techniques

27. Improving Agricultural Observatory: World Bank Supported

28. Agricultural Observatory Platform provides
• 6756 virtual weather stations in 9x9 Km square array (polygon)
• Climate/ weather Predictions ( Precipitation: chances, amount, etc.)
• What has happened (past years, months, days)
• Long Term trends Vs Current patterns (location specific)
• Pest & Disease forecasts

29. Expected Precipitation
Kenya, Next 7 Days
• Areas expected to have above normal rainfall in
the next 7 Days (11th-18th Nov, 2018) include:
1. Makuyu 10434998
2. Nyeri County 10454080
3. Elgeyo-Marakwet County 10276530
4. Bungoma County 10244289
5. Homa Bay County 10363100
6. Kirinyaga County 10367158
7. Muranga County 10377449

30. Kenya Rainfall Distribution – October/Nov 2018
Past 30 days – Sep 29 to Oct 29 7 days Forecast – Oct 29 to Nov 04
Key

31. Total Precipitation
by Location in
Kenya: Sept 28 to
Oct 28
NB: LTN gives the average values for
the last 7 years (2011-2017)
Implication:
More Locations in Kenya have received below normal rainfall between Sep 28 to Oct 28

32. Current vs
LTN at
Mirogi,
Homabay
Graph 1: Current accumulated rainfall from June for Mirogi is below the Normal (compared Long term average for the last 7
years)
Graph 2: Temperature for Mirogi is very close to the long term normal, shooting to above normal in mid October
Graph 3: Ratio of current precipitation(p) to potential evapotranspiration (PET) is below the normal for the month of October
Graph 4: The precipitation is close to the normal for the month of October, shooting to higher than normal from mid
October but falling to below normal towards the end of November. The trend is expected to continue in the first week of
November

33. Precipitation-
Past 30 days
Kenya

34. Precipitation Figures-
Past 7 Days, Kenya
Areas which received above normal rains include:
10491111-lat-3.375, long38.542- Taita Taveta County, Kenya
10333779-lat-0.958, long34.625-Gucha, Kenya
10368366-lat-0.042, long37.292-Meru County, Kenya
10433854-lat-0.375, long35.292-Kericho County, Kenya

35. The idea Pawa-Farm: Platform for Agro-Weather Advisory Services to Farmers

36. Pawa-Farm: Context specific advisory to a farmer

37. Pawa-Farm: Weekly Weather Forecast to a specific farmer

38. Pawa-Farm: Land Use recommendation to a farmer

39. Practical examples:
After applying good farming recommendations from
Online platforms

40. Kenya Climate Smart Agriculture Project: BIG DATA (WB)
• Big Data
Infrastructure
Established
Developing Integrated
Weather and Market
Information System
 Climate/weather Data
Generation Activities
 Data Analytics Activities
 Development &
Dissemination of Data
products & services
 Provision of data-driven
evidence for decision
making
 Training (making sense
from climate/weather
data)
 Provision of geo-
referenced & context
specific information

41. Agricultural Datasets Geospatial
datasets
Various
data sources
Big Data
Storage
Farmers
/PastoralistsStakeholdersField Extension Officers
Policy maker Agricultural
Researchers
Climate/Weather Crop
Modelling,
 Data Mining
 Machine Learning
 Analytics
Stakeholders:
SMS,
Bulletins,
Interactive Voice
Response(IVR)
WWW
Radios
TVs
Weather data
Field station
agricultural
data
Market data
Remote Sensing
data
e.g. NDVI
Other Weather data
-Triangulations
PROPOSED BIG DATA FRAMEWORK & DATA ECOSYSTEM:
World Bank Supported
Climate data
Farming Practices information

42. A Framework for sustainable management of agricultural research data
Data Ingestion
Exception handing
Data access
D AT A L AK E S ( D AT A S T O R AG E )
Analytic engineSimulation &
Modelling
Pipeline
processing
Content Registry
Workload scheduling
and execution
Meta data
catalogue
Data Governance
Data storage
Data Capture
Data organization
Data Quality
Feed Management
Visualization
Indexing
Machine learning
Sentiment Analysis
Natural language
processing
Explorative data analysis
Agro weather
query
Big Data platform development for climate Smart
Agriculture in Kenya
BDA Inference Engine (HPC/Big Data Analytic)
Analytic engine
PROPOSED DATA MANAGEMENT AND ANALYTIC MODEL FOR KENYAN AGRICULTURAL
DOMAIN

43. Effective CSA –must answer these questions- to
make the right decision
43
• What works?,
• Why does it work?,
• When does it work?,
• Where does it work?,
• How does it work?, and
• For whom does it work?

44. % of Reach
• More than 8M download of KALRO mobile apps
• Web portal access is also high
• SMS and USSD are used
• Ratio of extension is 1:1,500 farmers in Kenya
• There are quite a good number of other initiatives in the country

45. GAPS & CHALLANGES
1. Need Funds to scale up “Digitization of the development of agricultural value chain in Africa”
2. Inadequate capacity in Data Analytics, Modelling and Generation of GIS ready climate information
3. Shortage of Data Scientists and crop/livestock/climate modelling scientists
4. Lack of proven business models to support commercialization, sustainability and scalability (Need
for micro driven initiatives and support)
5. Need for User Research and Feedback Analysis to establish level of impact and change of
digitalization and provision of e-climate/e-weather information services in Kenya

46. NEXT STEPS
1. Development of Big Data Platform for Agriculture in Kenya to be
replicated in other African Countries
2. Fund raising to support scalability and sustainability of ICT
innovations & disruptive technologies in Agriculture
3. Seek for Collaboration and partnership opportunities specifically
with European Commission funded projects in Africa (e.g. EU Copernicus
programme)
4. Need for funds to support Kenya Agricultural and Livestock Research
Organization (KALRO) GIS (Geospatial) Data Cube – KGDC proposed &
e-climate/weather information service provision projects

47. Thank You & God Bless you