DAAfrica2024

Workshop on Data Science for Agriculture in Africa
November 23, 2024

Workshop supported by ASDS, #DigitAg and the MOOD project

Event affiliated with CARI’2024 (https://www.cari-info.org)
Bejaia, Algeria (hybrid)

PROGRAM : NOVEMBER 23, 2024

14h – 14h15: DAAfrica’2024 Introduction (Paulin Melatagia, Mathieu Roche)

14h15 – 14h35: Moses Muga and Ruth Njoroge; Seed Pelleting Technology on Spider Plant Seed

14h35 – 14h55: Akouyo Yvette Gbedevi, Kossi Atchonouglo, Marie-Ange Manier and Sid Lamrous; Crop Rotation Problem, The significance of the planning horizon duration and Fertilization with plants

14h55 – 15h15: Andé Mbairanodji, Founadoudou, Daquin Cédric Awouafack and Garba Bouba Boiga; Towards the digitalization of Cameroonian agriculture: current situation, challenges and prospects

Coffee break

15h40 – 16h: Marouane Kihal, Lamia Hamza and Mohammed Charif Kihal; Advanced Binary Classification for Disease Detection in Trees Using a novel Machine-Deep Learning method

16h – 16h20: Kinyua Gikunda and Nicolas Jouandeau; Optimized Lightweight Deep Learning Techniques for Precise Weather Prediction and Forecasting in Africa

16h20 – 17h20 Short presentations (15 minutes):

– Dagbelou Vinablo Kodjo Doinique, Bah Souleymane, Adekambi A. Souleymane and Yabi A. Jacob; Bibliometric and economic analysis in precision agriculture

– Belayneh Dejene, Gizachew Setegn and Selamawit Belay; Explainable and Interpretable Dry Beans Classification using Soft Voting Classifier

– Agouanet Franklin Platini and Tewa Jeanjules; Effectiveness of Image Processing Techniques in the Cultural Control of Fungal Plant Leaf Diseases

– Djènaton Kpadonou Ambroise Houedjissin, Sèmèvo Arnaud R. M. Ahouandjinou, Manhougbé Probus A. F. Kiki, François-Xavier Ametepe and Marc Kokou Assogba; Lightweight segmentation of UAV images for early detection of maize leaf diseases

17h20 – 17h30 DAAfrica’2024 Conclusion (Paulin Melatagia, Mathieu Roche)

ACCEPTED COMMUNICATIONS

– Kinyua Gikunda and Nicolas Jouandeau Optimized Lightweight Deep Learning Techniques for Precise Weather Prediction and Forecasting in Africa

– Marouane Kihal, Lamia Hamza and Mohammed Charif Kihal Advanced Binary Classification for Disease Detection in Trees Using a novel Machine-Deep Learning method

– Andé Mbairanodji, Founadoudou, Daquin Cédric Awouafack and Garba Bouba Boiga Towards the digitalization of Cameroonian agriculture: current situation, challenges and prospects

– Dagbelou Vinablo Kodjo Doinique, Bah Souleymane, Adekambi A. Souleymane and Yabi A. Jacob Bibliometric and economic analysis in precision agriculture

– Belayneh Dejene, Gizachew Setegn and Selamawit Belay Explainable and Interpretable Dry Beans Classification using Soft Voting Classifier

– Agouanet Franklin Platini and Tewa Jeanjules Effectiveness of Image Processing Techniques in the Cultural Control of Fungal Plant Leaf Diseases

– Akouyo Yvette Gbedevi, Kossi Atchonouglo, Marie-Ange Manier and Sid Lamrous Crop Rotation Problem, The significance of the planning horizon duration and Fertilization with plants

– Djènaton Kpadonou Ambroise Houedjissin, Sèmèvo Arnaud R. M. Ahouandjinou, Manhougbé Probus A. F. Kiki, François-Xavier Ametepe and Marc Kokou Assogba Lightweight segmentation of UAV images for early detection of maize leaf diseases

– Moses Muga and Ruth Njoroge Seed Pelleting Technology on Spider Plant Seed

CALL FOR SHORT PAPERS

SCOPE

Data science in agriculture has evolved with the accessibility of data by farmers that allow them to analyze and facilitate decision making. Today new technology like Internet of Things (IoT) enables us to collect and store farm and environmental data (e.g. soil data, water data, etc.) in dedicated databases and/or data warehouses. This agricultural data can be combined with other data sources (e.g. remote sensing, weather stations, web and social media, etc.) that need to address new challenges like ingestion of heterogeneous data.

Data science in agriculture aims to explore and mine agricultural data using different techniques like machine learning, deep learning, computer vision, text-mining, large language models (LLM), etc. For instance, data science can predict crop yields and plant and animal diseases with different variables, including rainfall, temperature fluctuations, and soil conditions by using a variety of data (e.g. sensor data, texts, satellites images, plant images, etc.).

So, agriculture professionals and decision-makers can use data science to provide information and knowledge in order to make decisions about agricultural activities in Africa.

TOPICS OF INTEREST

The topics of the workshop encompass all aspects concerning the intersection of data science and agriculture in Africa with different applications:

Smart Farming
Yield and production
Plant specie identification
Land cover monitoring
Crop recommendation
Crop monitoring & forecasting
Animal and plant health monitoring
Agroecology and water management
Food safety & security
etc.

SUBMISSIONS

Researchers, academics, and students working on the field of data science with application in agriculture in Africa are invited to submit short papers for oral presentations or posters. Submitted abstracts must be in English and will be reviewed by the workshop committees for suitability and interest to the DAAfrica audience. The authors can submit papers of unpublished work reporting original and early results, introducing new ideas or describing prototypes.

Every accepted submission must have at least one author registered for the workshop. All submitted extended abstracts must follow the LNCS format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guideline) with a page limit of up to 6 pages including the title page, figures, references, and an optional appendix. The abstracts should be submitted electronically in PDF format via EasyChair via the following link: https://easychair.org/conferences/?conf=daafrica2024

Accepted extended abstract will be published as CEUR proceedings. Selected contributions will be invited to submit full papers to ARIMA Journal (indexed by DBLP and DOAJ) for a peer-review according to its usual reviewing process.

IMPORTANT DATES:

Submission deadline: August 18, 2024
Notification to authors: September 23, 2024
Workshop date: November 23, 2024

PARTICIPATION

The workshop will be held in Bejaia, Algeria, as an event affiliated to CARI’2024. This workshop will be a hybrid event that combines a “live” in-person event with a “virtual” online component.

WORKSHOP CHAIRS

Paulin Melatagia, University of Yaoundé I, Cameroun
Mathieu Roche, CIRAD, UMR TETIS, France