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Sentiment Analysis for the Zindi Africa COVID-19 Tweet Classification Challenge WORKSHOP
Today, on June 23, 2023, at the EPAL Lab, a sister lab of YEESI Lab, we had a training session on NLP, specifically focusing on Sentiment Analysis for the Zindi Africa COVID-19 Tweet Classification Challenge. This competition provided an opportunity to enhance our skills in handling data compared to the recent hackathon, the Customer Sentiment Analysis Challenge for the Telecom Sector in Tanzania, which concluded just a day ago. In that competition, the YEESI Lab, along with our sister lab EPAL, achieved fourth place with the outstanding performance of Ms. Jackline.
During today's session, we had participants Mwajabu A Mgamba and Gervas Abel Lusele, among others, who shared their thoughts and experiences.
Mwajabu A Mgamba, a third-year student at Sokoine University of Agriculture in Irrigation and Water Resources Engineering, said "My name is Mwajabu A Mgamba. Today, in the Yees Lab, we learned about the modifications to the previous training regarding sentiment analysis and how to train COVID-19 tweet analysis. Now we have expanded our knowledge on training and testing these analyses".
Gervas Abel Lusele shared his insights, stating, "My name is Gervas Abel Lusele. Today's session revolved around the Zindi challenge, which involves creating and training a model to analyze the sentiment of COVID-19 tweets. We discussed the code used in the previous IndabaX challenge, specifically focused on sentiment analysis for telecommunication tweets in Tanzania. Drawing on our knowledge from that challenge, our goal is to develop a superior model that accurately predicts the sentiment of COVID-19 tweets. We aim to build upon our previous experience and utilize the insights gained to create the best possible solution for analyzing sentiments related to the pandemic."
These participants, along with the rest of the group, are motivated to apply their newfound knowledge and skills to excel in the Zindi Africa COVID-19 Tweet Classification Challenge. By leveraging their expertise and incorporating grammatical English, they are determined to create a top-performing model and contribute to the field of sentiment analysis during the ongoing pandemic.
23 June 2023
Ms Jackline received a certificate of excellence from YEESI Lab PI during the event.
A female yeesi lab student leads in tanzania indabax hackathon 2023
Congratulations to Ms. Jackline Ulenje, studying BSc in Irrigation and Water Resources Engineering, SUA for her achievements in the Tanzania IndabaX Hackathon 2023 and the SUA YEESI Lab! Placing 4th in the Tanzania IndabaX Hackathon is a great accomplishment, and it shows her skills and dedication in the field of hacking and problem-solving. Additionally, securing 1st place in the SUA YEESI Lab further demonstrates her expertise and the recognition she has received for her model. It's fantastic to see Jackline's hard work paying off, and I wish her continued success in her future endeavours.
Congratulations to Mr Barnabas Nsonga and Mr Stephano Mashauri for placing 2nd and 3rd in the hackathon. You have devoted so much invaluable time to learning and improving your Machine Learning skills.
Keep it Up!
22 June 2023
tanzania indabax hackathon 2023 take off at sua
It feels so good to hear that students at Sokoine University of Agriculture (SUA) are participating in the Tanzania IndabaX Hackathon 2023! Hackathons provide an excellent platform for students to showcase their skills, creativity, and problem-solving abilities in the field of machine learning.
The Tanzania IndabaX Hackathon is an exciting event that brings together aspiring data scientists, researchers, and technology enthusiasts from across Tanzania. Participants collaborate in teams to tackle real-world challenges using machine learning techniques and methodologies. These challenges could range from data analysis and predictive modelling to computer vision and natural language processing.
Participating in hackathons like Tanzania IndabaX Hackathon 2023 allows students to apply their knowledge of machine learning algorithms, data preprocessing, feature engineering, and model evaluation in a competitive and time-constrained environment. They have the opportunity to work with large datasets, explore various machine learning frameworks and libraries, and implement innovative solutions to solve complex problems.
Hackathons not only foster technical skills but also promote teamwork, communication, and critical thinking. Students will collaborate closely with their teammates, sharing ideas and expertise to develop creative solutions. They will also have the chance to network with industry professionals and mentors who can provide valuable guidance and insights into the field of machine learning.
By participating in the Tanzania IndabaX Hackathon 2023, students from Sokoine University of Agriculture will gain practical experience, enhance their problem-solving abilities, and broaden their understanding of machine learning applications. It is an exciting opportunity for them to showcase their talent, learn from their peers, and contribute to the advancement of data science in Tanzania.
With the support from the YEESI Lab project and EPA Lab, the event will continue from tomorrow 20th to the 21st of June 2023 at Mazimbu Video Conference Room in which each student will be training models individually and submitting them.
Wishing all the participants from SUA the best of luck in the Tanzania IndabaX Hackathon 2023!
STUDENT'S WORKSHOP ON Natural Language Processing (NLP) and Sentiment Analysis AT EPA LAB PREMISES
The Electronics and Precision Agriculture Lab (EPAL Lab), a sister lab of YEESI Lab, held a session on Sunday, 18th June 2023, that was focusing on Natural Language Processing (NLP) and Sentiment Analysis. The workshop was led by Mr Dickson Massawe, a 4th year Ag Engineering student. The team successfully fine-tuned a pre-trained model from Hugging Face specifically for AutoTokenization, enabling them to classify SMS messages as either spam or ham. This process involved training the model on a labelled dataset of SMS messages and optimizing its ability to accurately differentiate between spam and ham messages. Sentiment analysis is a valuable technique in NLP that allows for the understanding and classification of the sentiment expressed in text data.
One of the participants, Ms Jackline Joel Ulenje, introduced herself as a third-year student at Sokoine University of Agriculture, specializing in irrigation and water resources engineering. During the YESSI Lab training session on June 18, 2023, Jackline expressed her engagement with Sentiment Analysis. She mentioned her ability to utilize various libraries, perform training on datasets, and conduct tests to effectively solve problems. This indicates her preparedness for the upcoming IndabaX competition, suggesting a solid understanding of the concepts and techniques covered during the session.
Another participant, Ms Mwajabu Mgamba, shared her insights from the session. They focused on the topic of sentiment analysis with Hugging Face, specifically discussing aspects such as word tokenization, changing label dummy variables, and label encodings. Word tokenization involves splitting text into individual words or tokens, which is a crucial step in many NLP tasks. Changing label dummy variables and label encodings are techniques used to represent and process categorical data in machine learning models. Mwajabu's comments suggest an understanding of the practical application of sentiment analysis using the Hugging Face library.
Overall, the EPAL Lab session provided participants with valuable knowledge and hands-on experience in Natural Language Processing and Sentiment Analysis. Through fine-tuning a pre-trained model from Hugging Face for AutoTokenization, the team was able to successfully classify SMS messages as spam or ham. The comments from participants like Jackline Joel Ulenje and Mwajabu Mgamba indicate their readiness for the upcoming IndabaX competition, demonstrating their proficiency in using libraries, training models, and applying various techniques in NLP.
STUDENT'S WORKSHOP ON MACHINE VISION AT EPA LAB PREMISES
Electronics and Precision Agriculture Lab (EPAL Lab), a sister lab of YEESI Lab, has shown remarkable progress in the machine learning training for the QoS Prediction Challenge by ITU AI/ML in the 5G Challenge. EPAL conducted a hands-on training workshop for SUA students (10 males and 3 females) on Saturday, 11/06/2023 which was done by Mr Dickson Massawe. With meticulous analysis of the dataset, they identified crucial features for accurate QoS prediction. By employing robust data cleaning techniques, EPAL Lab ensured data integrity and reliability, enhancing the quality of predictions. Through continuous evaluation and refinement, their team achieved exceptional results, surpassing the challenge benchmark.
Members of EPAL Lab showcased expertise and innovation in model training, highlighting their excellence in machine learning. They created accurate submission files adhering to challenge requirements and promptly submitted them, validating the quality and reliability of their trained model. EPAL Lab's remarkable progress and dedication position them as strong contenders, eagerly awaiting evaluation and results, confident in their positive impact on the field of machine learning.
The students submitted solutions to the web; https://zindi.africa/competitions/qos-prediction-challenge/leaderboard
YUNEEC H520E Commercial Hexacopter at sua premises
It is exciting news that the Yuneec H520e drone has been delivered to the Lab for multispectral data collection in the field of machine vision work. The availability of this advanced drone technology will significantly contribute to research and analysis in agriculture in Tanzania.
The objective of utilizing the Yuneec H520e drone is to gather multispectral data that will aid in validating theories related to crop emergence, crop vigor measurement, and identification of crop failure caused by pests or diseases. By capturing high-resolution images from the drone, researchers will be able to visualize and analyze the crops, further enhancing their understanding of crop characteristics.
The YEESI Lab students will have the opportunity to work with UAV imagery data and gain practical experience in analyzing and interpreting crop-related information. They will learn how to leverage artificial intelligence (AI) programs to characterize crops, estimate crop vigor, identify crop failure, and even count seedlings. This hands-on experience will not only enhance their technical skills but also foster a deeper understanding of precision agriculture and its applications.
The drone is currently located at the Electronics and Precision Agriculture Lab, providing a centralized location for students and researchers to access and learn about unmanned aerial vehicles (UAVs). This facility will serve as a hub for exploring the potential of drone technology in agricultural research, offering valuable insights into the field of precision agriculture.
It is noteworthy that the Yuneec H520e drone is the first of its kind to be delivered in Tanzania, making it a significant milestone for the country's research and technological advancements in agriculture. The introduction of this cutting-edge drone technology opens up new possibilities for data collection, analysis, and decision-making processes in the agricultural sector.
Overall, the arrival of the Yuneec H520e drone to the Lab marks a significant step forward in the application of UAV technology for agricultural research and analysis in Tanzania. The opportunity for students to engage with this advanced equipment and explore the potential of UAV imagery data will undoubtedly contribute to their academic and professional growth, as well as to the advancement of precision agriculture practices in the country.
3rd June 2023
HR Management for start-ups
This time at our YEESI Lab Weekend Workshops Series, we had an opportunity to have Madam Regula, a Principal HR officer train us on Human resources management for start-ups. Madam Regula was keen to train us to work with human beings with diligence while achieving start-up goals.
It should be noted that most successful start-ups were smart in recruiting the best brain and networking with people in achieving the vision and execute missions successfully.
Madam trained on 19 principles of HR from recruitment to all stages of completing daily tasks. The upcoming "CEO" from YEESI Lab learnt the other side of achieving goals apart from the normal Artificial Intelligence discussions.
More than 34 registered and attended the workshop. 30% of them were female. 65% of them have never worked on managing humans in a company setting.
3rd June 2023
Flashback to the YEESI LAB open courseware
1. Dr. Kadeghe Fue
2. Mr. Deus Francis
3. Ms. Catherine Mangare
4. Dr. Alcardo A. Barakabitze
5. Dr. Sixbert K. Maurice
6. Ms. Rehema Mwawado
7. Mr. Hussein Mkwazu
8. Mr. Joseph Telemala
9. Dr. Michael Mahenge
Mr Fikiri Matatizo, a YEESI Lab and 3rd year PIT Student at Sokoine University of Agriculture placed first in a pitch competition that was conducted at the National Carbon Monitoring Centre (NCMC). Mr Fikiri presented his final year project in which he is developing a "Plant Diseases Detection and Monitoring App". This mobile app is using machine vision technology (AI-based) to detect diseases affecting tomato plants. Mr Fikiri is using the YEESI dataset to train the model. The app is based on Flutter technology with its backend using TensorFlow Lite. Mr Fikiri is advised on this project by the YEESI Lab PI, Dr Kadeghe Fue.
The pitch competition awarded the leading candidate with 1.5 Million TZS and the winner certificate, the 1st runners-up took 1.0 Million TZS while the 2nd runners-up took home 0.5 Million TZS.
Congratulations Mr Fikiri for the milestone achieved. The sky is the limit.
for more information, http://suamedia1994.blogspot.com/2023/05/sua-yaboresha-mitaala-yake-kuzalisha.html
The Tanzanian agriculture industry faces a great challenge caused by pests and diseases threatening food security. Pests such as tomato leaf miners, aphids, fall armyworms (FAW), and bean leaf miners devastate crops. Also, diseases such as maize streak virus, early blight, Powdery mildew, Leaf spot, Rusty brown leaf, foliar disease, Bacterial Wilt, Blossom end rot, Flower abortion, Leaf Curl and Black rot have caused the crop failure that leads to yield reduction. So, precisely and accurately detecting such pests and diseases to improve agriculture productivity in the country is paramount. However, manual detection is cumbersome, time-consuming and costly. So, automating the procedure using machine vision technologies is necessary for sustainable prosperous agriculture.
Therefore, this dataset presents the first Tanzanian agricultural classification dataset that contains 7992 healthy and unhealthy crops images (maize, beans, green peppers, onions, okra, watermelons, sunflowers, African eggplants, tomatoes, Chinese cabbage, hot peppers, wheat, leaf kale and cabbage). Images were collected in real-world conditions in Morogoro, Tanzania, in August and September 2022, using smartphones and professional GoPro Hero 9 cameras. The dataset is called YEESI Dataset. It is used as Open Data. The authors expect this dataset to revolutionize applications of Artificial Intelligence (AI) in agriculture for evaluating classification models related to crop pests, diseases and weed problems from open data.
The dataset can be found here: doi: 10.5281/zenodo.7729285 or here https://www.zenodo.org/record/7729285
It can be cited as; Fue, Kadeghe, Barakabitze, Alcardo, Geofrey, Anna, Lebalwa, Bertha, Lyimo, Neema, Mwaipaja, Faraja, Jonathan, Joan, Mbacho, Susan, Sanga, Camilius, Rains, Glen (2022) The YEESI Lab Dataset. doi: 10.5281/zenodo.7729285
RESTUTA GEORGE insights on yeesi lab weekend
My name is Restuta George, I am a first-year student at Sokoine University of Agriculture pursuing a Diploma in IT. My experience at the YEESI Lab Weekend provide me with exposure to understanding what machine learning actually is and how it can help to solve problems facing societies, as well as techniques involved in machine learning. The weekend was an amazing opportunity to learn and enhance my skills in artificial intelligence, data science and machine learning. I am committed to working hard on AI/ML .so that I can be able to solve real-world problems. Thanks
By Restuta George, 08-May-2023
ibrahim meshack insights on yeesi lab weekend
During the YEESI lab weekend, I experienced many things in machine learning;
By Ibrahim Meshack, 08-May-2023
Stephano is standing 2nd left..
STEPHANO MASHAURI INSIGHTS ON YEESI LAB WEEKEND
The YEESI lab competition that took place extensively for about two days has introduced me to the world of extreme programming and software development, and how hard and challenging coding can be.
I actually didn't know how artificial intelligence and machine learning worked well and as a beginner I realized where to start, python packages, and engineering features which seems to be more complicated during the competition,
Up to date, I believe I can improve and become good Artificial Intelligence tech developer.
By Stephano Mashauri, 08-May-2023
dickson massawe insights on yeesi weekend
Predicting biomass from satellite images is a challenging and important task in the field of remote sensing and environmental monitoring. By working on this project, I have likely gained valuable experience in various aspects of machine learning, such as data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Specifically, I may have learned techniques for handling large and complex datasets, extracting relevant features from remote sensing data, dealing with imbalanced and skewed data, and selecting appropriate machine learning models for regression tasks. I may have also gained insights into the use of convolutional neural networks (CNNs) for image processing and deep learning.
Overall, the skills and knowledge I acquired during this project can be applied to a wide range of machine-learning tasks in various domains, such as environmental monitoring, agriculture, and forestry. These skills can help me become a better data scientist and make meaningful contributions to the field of machine learning.
By Dickson Massawe, 08-May-2023
YEESI LAB WEEKEND OF Satellite Machine Vision HackathoN was CONCLUDED with flying colors. Congrats STudents!
YEESI lab weekend was concluded in style where the best-performing students were awarded prizes. Mr Dickson Massawe, Mr George Munishi and Mr Fikiri Matatizo consecutively performed extraordinarily and amassed home the whole YEESI Lab fortune. The YEESI Lab team send their appreciation to all participants. Their eagerness to win was everything that we were building for the past two years. We wish our students all the best as they continue competing in Africa Biomass Challenge and take the $10,000 prize that has been allocated for this competition by GIZ.
Machine learning hackathons can be important to improve students' understanding of machine learning in several ways. Firstly, hackathons offer students an opportunity to apply their theoretical knowledge to real-world problems, helping them to develop practical skills and gain hands-on experience in machine learning. Secondly, hackathons provide an environment for students to collaborate with peers and experts in the field, promoting teamwork and networking. Finally, hackathons can help students to build their confidence in their abilities and to learn from their mistakes, enabling them to approach future challenges with a growth mindset. Overall, machine learning hackathons can be a valuable tool for students to develop their skills and deepen their understanding of the field.
View Album: https://photos.app.goo.gl/5nEzC94mZekpzJ8c9
Mr Dickson Massawe, a 4th-year Agricultural Engineering student who placed first in the hackathon
Mr George Munishi, a 4th-year Agricultural Engineering student who placed second in the hackathon
Mr Fikiri Matatizo, a 3rd-year Physics and Information Technology student who placed third in the hackathon
YEESI LAB WEEKEND: Weekend of Satellite Machine Vision HackathoN [5TH, 6TH AND 7TH mAY, 2023]
An AI Hackathon Invite for members of YEESI Lab
CONGRATULATIONS COMMENTS FROM SOKOINE UNIVERSITY OF AGRICULTURE (SUA)
Sokoine University of Agriculture YEESI Lab team participated in the UmojaHack Africa Hackathon 2023 https://umojahack.africa/. YEESI Lab student, Adam Jamali, a 3rd-year Irrigation student, placed third in the hackathon. The winners can be found here; https://zindi.africa/competitions/umojahack-africa-2023-beginner-challenge/leaderboard
Among other teams that we had, YEESI Lab had a team, formed by three other students (Mr Dickson Massawe, a 4th-year Agricultural Engineering student, Mr Fikiri Matatizo, a 2nd-year Physics and IT and Mr George Munishi, a 4th-year Agricultural Engineering student), which excellently with synergy represented well our lab with outstanding flying colours. Stephano Mashauri, a 2nd-year Agricultural Engineering student also placed seventh in the competition. Mr Jacob Shimba, a third-year Agricultural Engineering student also participated well in the competition. The students were supervised closely by Mr Deus Francis from the Department of Informatics and Information Technology. The team did well in all the challenges in Tanzania as shown in the public leaderboard http://zindi-metabase-v1.azurewebsites.net/public/dashboard/b9115882-27e0-4654-9f40-31beece000da
Most of our YEESI Lab students utilized YEESI Lab public shared Computing Node http://yeesi.sua.ac.tz/ to train the models.
Congratulations to our hard-working students
The hackathon involved 3000 students across 30 African countries and more than 300 universities. It was done online for two days from 18-19 March 2023 [Super Weekend]. The YEESI Lab students were positioned in the YEESI Lab premises at the Electronics and Precision Agriculture Lab, School of Engineering and Technology, Sokoine University of Agriculture.
The challenge was on Carbon Dioxide Prediction.
The Description of the challenge
The ability to accurately monitor carbon emissions is a critical step in the fight against climate change. Precise carbon readings allow researchers and governments to understand the sources and patterns of carbon mass output. While Europe and North America have extensive systems in place to monitor carbon emissions on the ground, few are available in Africa.
The objective of the challenge is to create machine learning or a deep learning model using open-source CO2 emissions data (from Sentinel-5P satellite observations) to predict carbon emissions.
These solutions will enable governments, and other actors to estimate carbon emission levels across Africa, even in places where on-the-ground monitoring is not possible.
YEESI Lab exclusively guides and trains students in Artificial Intelligence for agriculture and other allied sciences.
The project team comprises of the YEESI Lab PI, Dr Kadeghe Fue and another YEESI Lab Data Team expert, Dr Neema Nicodemus Lyimo to represent YEESI Lab. The team also includes Dr Silvia F. Materu, a lecturer from SUA and Dr Ndimile C. Kilatu, a Morogoro Municipality Health Officer from TAMISEMI. Congratulations Team.
From Lacuna website, the announcement says:
Tanzania is one of the fastest-growing economies in Africa and bears a lot of potential in many areas, one of them being innovation. This promising and dynamic area has seen rapid developments in the last few years as the country moved 26 places up on the Global Innovation Index, from ranking 123 in 2013 to 97 in 2019.
However, while Tanzania's innovation performance has improved, startups struggle to grow and scale. One of the major issues is the lack of systematic approaches for collecting, storing, and disseminating key information about the key actors in the innovation and entrepreneurship space. Those wishing to support actors in this sector must rely on competitions and public calls to solicit interests. Further, while entrepreneurship support organisations (ESOs) keep records of startups they work with, the information is often for the most current programs and rarely shared with the ecosystem. The information gap also persists in relation to entrepreneurship support organisations (ESOs). It is unclear what actors provide services and for which type of enterprises. Likewise, no consistent source disseminates both local and international opportunities.
Being an apex body in the ecosystem, the Tanzania Startup Association (TSA) is identifying and profiling ecosystem actors for the annual status of the startup ecosystem. The information collected from this activity will be shared widely within and outside the ecosystem to inform priorities towards developing better interventions and promoting synergies.
In this regard, the TSA requests startups, incubators, accelerators, fabrication labs, maker spaces, capital providers, academic institutions, regulatory agencies, and other actors operating in Tanzania's startup ecosystem to share their information by filling out this form. Start by selecting the category most relevant to your organisation's activities, and actor-specific questions will follow up. However, all information shared here shall not be distributed to third parties without your consent.
In case of any concerns, please contact them through email@example.com and include "Ecosystem Actors Identification and Profiling 2022" in your email subject.
Mr Dickson Massawe operating the modern SnapMaker 3-in-1 A350T, a 3D printing, CNC carving and Laser engraving machine at the Electronics and Precision Agriculture Lab (EPAL). EPAL develops automation technologies and sensors for Precision Agriculture.
IndabaX: A way to experiment with the ways in which we can strengthen our Machine Learning community, and to allow more people to contribute to the conversation. The IndabaX programme started in 2018 as an experiment in strengthening our machine learning community beyond the annual Deep Learning Indaba, to allow more people to contribute to the conversation on artificial intelligence and machine learning. We join hands across our beautiful continent Africa. The initiative continues in 2022, and it is YOUR initiative!
An IndabaX is a locally-organised Indaba (i.e gathering) that helps develop knowledge and capacity in machine learning and artificial intelligence in individual countries across Africa.
A Deep Learning IndabaX is a locally-organised Indaba that helps spread knowledge and builds capacity in machine learning.
TZ IndabaX in Tanzania is organized by Tanzania AI Lab in collaboration (co-hosted) with Nelson Mandela Institution of Science and Technology, AI for Development Lab at the University of Dodoma and dLAB at the University of Dar es Salaam.
See the presentations here: https://docs.google.com/presentation/d/16-k3YN7kGziBOtNQEU3Dt37YvCOznxAjrb3lqWXvsso/edit?usp=sharing
You can register and participate in challenges: https://geoaichallenge.aiforgood.itu.int/match/matchitem/64
The PI, Dr Kadeghe Fue was invited to attend the 1st Enhance Mind Artificial Intelligence (EMAI) conference which happening from 14th to 16th November 2022 held at the COICT University of Dar es Salaam as a Key Note Speaker.
The PI presented his ideas on YEESI Lab research and shared with innovators on gaps available that can be solved by using Artificial Intelligence technologies that are relevant to the majority of the farmers and that are posed to change farming in Tanzania. He talked about how AI experts can position themselves in Digital Economy and contribute to the targets of the National Five-year Development Plan (FYDP) III.
Last week three staff from USAID & PEER visited SUA for M & E assignment. At SUA, there are three projects which are or have already been funded by them. These are:
a. Exploring the fate of mercury in artisanal gold mining of the Lake Victoria Gold Field under Principal Investigator (PI), Prof. Clavery Tungaraza - https://sites.nationalacademies.org/PGA/PEER/PEERscience/PGA_181434
b. Enhancing postharvest technologies and food safety innovations in fresh tomato value chain under PI, Yasinta Muzanila - https://sites.nationalacademies.org/PGA/PEER/PEERscience/PGA_195550
c. Morogoro youth empowerment through establishment of social innovation (YEESI) lab for problem-centered training in machine vision under PI, Dr. Kadeghe Fue - https://sites.nationalacademies.org/PGA/PEER/PEERscience/PGA_365059
First the M&E team from USAID and PEER with the Principal Investigators of funded project made a courtesy call to the office of Vice Chancellor (VC). Then they visited the Electronics and Precision Agriculture Lab (EPAL) at School of Engineering and technology (SoET) before visiting the SMC.
At SMC, they had meeting with PI’s for the three projects with their respectively research team members. The presentation was based on what has been done to accomplish the research objectives as stipulated in the approved proposal. Also, there were question and answer session (Q&A).
After the presentation and Q&A session, they made a visit to Prof Tungaraza’s lab.
In concluding their assignment, they gave a well done job to all their projects. They were real impressed by the outstanding results, outcome and impacts.
At last, the three staff from USAID & PEER had a courtesy call to the office of Principal of CoNAS, Dr Karugila.
YEESI Lab PI meets K.I.E.Z, an initiative dedicated to facilitate entrepreneurs in AI with scientific expertise as well as access to capital, industry partners and hiring talent. From the first idea to the successful business, we provide science-based AI startups with everything they need to grow fast and sustainably.
YEESI Lab PI Dr. Kadeghe Fue, Dr. Susanne Perner, and Mr. Jonathan Zebhauser discussed on conducting an activity that will involve SUA students especially who are working with YEESI Lab together with other four Germany universities; Technische Universität Berlin, Humboldt-Universität zu Berlin, Freie Universität Berlin and Charité Universitätsmedizin.
The activity will be working on real-world challenges to smallholder farmers in Tanzania: students will be grouped in interdisciplinary and international teams and will learn how to transform business ideas into an early business concept using AI technology.
The event will tentatively happen 23rd - 24th November (all-day).
Ms Faraja and Dr Neema with Ihenge farmers and Extension Officers
Ms Faraja and Dr Neema Nicodemus, members of the academic staff at SUA, were in charge of Gairo District data collection. They have taken pictures of five different crops. That is, spinach, bell pepper plant (Capsicum annuum), Brassica Chinensis, tomatoes, and maize from four wards in the district. Data on bell pepper plants, Brassica Chinensis, and maize were collected from Chigela village in the Ihenje ward. The crops are frequently affected by diseases like Bacterial leaf spots, Mosaic virus, Fusarium wilting disease (which affects plants from the roots), and Fall Armyworm in Maize.
Ms Susan Mbacho, a member of the academic staff at SUA, was privileged to be part of YEESI Lab DATA team. Ms Susan visited Mgeta ward located in Mvomero district, Morogoro Region in Tanzania. Ms Susan found out there were various crop species grown. With the assistance of an extension officer, Mr Eliewaha Venance Kivunge, they were able to visit fields with various crops. The crops include, among others, vegetables such as Cabbage, Green Pepper, carrot, and ‘Ngogwe/ Nyanya chungu’. During the field visit a number of farmers’ fields had grown cabbages. A number of plants were healthy in most of the fields visited, however they found unhealthy plants with pests or diseases as well. The disease which was prevailing in most of the field is black rot. There were also cabbage pests found, which caused the plant leaves to be damaged. Also, there were plants identified with deficiency of nutrients such as Phosphorus and Calcium. A very interesting dataset was collected and classify by the Extension Officer who is an expert in agriculture.
This is the first team to bring Nutrient Deficiency images for training. YEESI Lab is excited to explore all such wonderful brought by the team.
Dr. Alcardo Alex Barakabitze and his team from the Sokoine University of Agriculture, RECODA and Sahara Ventures announced among the winners of the Artificial Intelligence for Agriculture and Food Systems (AI4AFS) Innovation Research Network in Africa with the project titled “Enhancing Farm -scale Crop Yield Predictions using Machine Learning Models for Internet of Agro- Things in Tanzania”. It is worth mentioning that accurate prediction of crop yields at the farm scale can help smallholder farmers to estimate their net profit and enable insurance companies to ascertain payouts and agri-related loans to farmers.
Dr Barakabitze, Dr Fue and Dr Banzi from left with UDOM colleague at the workshop
The AI4D Multidisciplinary Research Lab is a project run in collaboration between two public academic institutions in Tanzania, The University of Dodoma (UDOM) & Nelson Mandela African Institution of Science and Technology (NM-AIST).
The AI4D lab presented a two-day workshop which took place from 10th-11th August 2022 conducted in hybrid (virtual and physical at the University of Dodoma, Dodoma - Tanzania). The workshop featured paper presentations, keynote talks, AI solutions demonstrations, and interactive panel discussions. The workshop explored issues around four thematic areas, namely: Healthcare, Environmental Conservation and Agriculture, Digital Economy and Small-Scale Enterprises, and AI Infrastructure and Data Ecosystem. Researchers, Innovators, Students, and Policymakers from across the continent participated.
YEESI Lab PI, Dr Kadeghe Fue and co-PI Dr Alcardo Barakabitze were among the people who were invited to present keynotes on AI for Agriculture and the work we do at YEESI Lab. See https://ai4dlab.or.tz/pages/ai4d-lab-workshop/speakers.html.
Dr Fue and Dr Barakabitze presented well for the YEESI Lab and demonstrated the way forward in the development and implementation of the AI-based machine vision systems in Agriculture.
18 August 2022
YEESI lab, in collaboration with the DICT office at SUA, shared one desk to demonstrate and exhibit work done by YEESI Lab.
Nane Nane Day on 8 August celebrates to recognize the important contribution of farmers to the national Tanzanian economy. Nane Nane means "eight eight" in Swahili, the national language of Tanzania (and of Tanganyika and Zanzibar, the two countries whose union created the United Republic of Tanzania in 1964).
Nane Nane also may refer to the Agricultural Exhibition, a one-week fair that takes place every year around this date [8/8] in varying locations of Tanzania. In the Nane Nane Agricultural Exhibition, farmers and other agricultural stakeholders (e.g., universities and research institutes, input suppliers or fertilizer producing industries) showcase new technologies, ideas, discoveries and alternative solutions concerning the agricultural sector. Nane Nane is a fair where government and private firms present their services and activities to the public.
Every year the national Nane Nane show takes place in different locations, for example in Ngongo, Lindi Region (2014), while there are also regional Nane Nane shows held in seven zones, namely in Arusha for Northern Zone; Eastern in Morogoro; Lake in Mwanza and Simiyu; Highlands in Mbeya; Southern in Lindi, Mtwara or Songea; Western in Tabora; and Central in Dodoma.
YEESI Lab was represented by Mr Matatizo, Mr Massawe, Mr Swai and Dr Fue, YEESI Lab PI. Posters and brochures were shared to NaneNane visitors. The YEESI Lab in turn collected good imagery dataset of horticulture nursery from the Crop Science and Horticulture Department Model Farms at Nane Nane.
From 18th to 22nd of July 2022, Data Science Africa (DSA) organized a workshop in Arusha, Tanzania, bringing together data science experts in Africa to discuss topics related to Data, Technology, and Community.
Dr. Kadeghe G Fue, a lecturer from Sokoine University of Agriculture and Project Leader of SUA YEESI Lab, was one of the Keynote Speakers invited to present on digital and precision agriculture research in Africa and the work SUA YEESI Lab is doing on Data Science.
His presentation explained the role of Data Science Research in Digital and Precision Agriculture for African countries and the importance of integrating super neat and intelligent data-driven innovations for smallholder farmers.
Prof Sanga, a YEESI Lab coPI attended a workshop on Creating Awareness on Open Science and Infusing it into Research Practice and Processes within Higher Educational Institutions in Eastern and Central Africa which took place at Multifunctional Hall of the Confucius Institute of the University of Dar es Salaam, Dar es Salaam, Tanzania from 14-15 July 2022.
Sokoine University of Agriculture is among of the three universities participating in the Innoversity Project. This project was launched by French Embassy. Other collaborators are University of Iringa and Nelson Mandela African Institution of Science and Technology.
About Call for University Entrepreneurs
The call for university entrepreneurs provides opportunity for university students both undergraduate and postgraduate with innovative business idea on agriculture particularly agri-food sector. The call focus on identifying startups at ideation ,prototype, or Minimal Viable Product stage that will lead to sustainable technology businesses and companies with high growth potential.
Successful startups will undergo an incubation program run by Sahara Ventures (https://saharaventures.com/) and thereafter will be linked to on-campus innovation hubs and technology transfer offices to encourage innovation, entrepreneurship, technology transfer, and research commercialization to create new solutions and employment opportunities.
About the Project
Innoversity project is a two-year project funded by the France Embassy in Tanzania and implemented by Sahara Ventures. The project supports students, lecturers, researchers, and management to integrate innovation and entrepreneurial approaches in their works to address the skills gap and create employment opportunities for youths.
Deadline for Applications: 20th August 2022
For more information about the call, visit https://forms.gle/3wnTnro9FVdSEAML6
In this Omdena, AI Challenge with the Global Partnership for Sustainable Development Data, we created a simple but powerful application using GEE images to estimate crop yield in Senegal.
For food security understanding the food system is essential. Accurate crop type details in near real-time will provide insights into the food system for policymakers and will provide information on crop diversity and nutrition outcomes. So, we decided to create an application using open-source satellite images to identify the crops and estimate the yields for any given area.
Follow the link below for Details:
Sokoine University of Agriculture (SUA) is a public and student-centered university continue to improve preparing students to be competent, professional and skilled graduate through training.The University integrate research, consultancy and technical operations to produce skilled labour force that can be employed or self-employed and contribute to the national, regional and global development as per National Five Year Development plan (FYDPIII) of 2021and SDG 1(no poverty),SDG 2 (no hunger), SGD 4 (quality education), SDG 8(Decent Work and Economic Growth). To impart required skills, confidence, experience and to establish, run and manage enterprises the University established SUA STEP program to empower students to self-employ, as a way to reduce unemployment.
Dr Kadeghe Fue, YEESI Lab PI, will address DSA Event in Arusha, Tanzania as a keynote speaker. He will discuss the role of data science in precision agriculture.
Data Science Africa, an NGO, is an important stakeholder in moving forward the agenda of digital agriculture for Data-driven agriculture. Dr Fue will commend their work and establish a strong collaboration with DSA on research and development. YEESI Lab will play a great role in promoting data science in Agriculture in Africa.
The event will take place from 18th to 22nd July 2022.
A University of the Western Cape (UWC) team has won an overseas trip to the US, with an additional three students claiming a cash prize of 100 dollars each.
This big win came at the annual USSAVI (US-Embassy SA Virtual Incubator initiative) entrepreneurship programme on 5 May 2022, where UWC claimed five of the eight available prizes.
The programme, sponsored by the US Embassy in South Africa, took competitors through the programme week by week, culminating in the pitching event.
Boost Up 2022 Application
Je wewe ni mbunifu? Usikose kutuma maombi ya kushiriki Shindano la BOOST UP kwa 2022. Maombi yamefunguliwa rasmi tarehe 1 Juni 2022 na yatahitimishwa tarehe 30 Juni 2022. Bonyeza link hii kukamilisha maombi yako
Morogoro Youth Empowerment through Establishment of Social Innovation (YEESI) lab hosts a renowned Prof in Precision farming
Sokoine University of Agriculture (SUA) has said that if there is sustainable use of Information and Communication Technology (ICT)in the country without restrictions then agriculture in this country can grow rapidly and be productive for the individual farmer and the Nation as a whole.
The YEESI Lab PI, Dr Kadeghe Fue was invited by Anzisha Venture Studios to speak on Innovation Week Tanzania 2022 (IWTz2022) Morogoro Region Edition which was commenced on Friday of 13th May 2022 at Morena Hotel, Morogoro. The PI spoke on a session titled "As the entire world is moving towards technopreneurship, what is the current state in Tanzania, and how does the regulatory environment and media support innovations, technology and startup entrepreneurship?"
The Guest of Honor was the Regional Commissioner Hon. Martin Shigella who was represented by the District Commissioner, Hon. Adv. Albert Msando.
The YEESI Lab PI discussed Digital Agriculture and the importance of using Machine Learning and Vision to improve the work of farming communities. He discussed the priorities mentioned in Tanzania's Five Year National Development Plan (FYDP III) that was presented by the Minister of Finance, Dr Mwigulu Nchemba on June 2021. FYDP III mentions Precision Agriculture, Artificial Intelligence and Innovation Hubs to be leading agendas for youth to unlock opportunities and improve agriculture.
The theme of the event was "Innovation for Sustainable Development".
13th may 2022
yeesi lAB Participates in sua innovation day
YEESI Lab PI,Dr Kadeghe Fue and students participated in SUA innovation day to showcase their progress on research to SUA Community and District Commissioner Adv. Albert Msando.
yeesi LAB participates in machine learning competition for an internship at zindi africa
Some of the YEESI Lab students and the PI participated in a machine learning competition [https://zindi.africa/competitions/loan-default-prediction-challenge] which provides winners with the opportunity to participate in an internship interview invitation. The Loan Default problem is among the most pressing issues for farmers that have led to high monthly premiums and unaffordable interests in farming society. One of the students who placed 6th, Mr. Fikiri, was invited for the interview. The PI participated in the competition independently to learn how to teach students to participate in the machine learning competition. The PI placed 3rd place (1st in Tanzania) and his code when run on Google Collab placed 1st on the leaderboard. The code will be used by students to learn how to efficiently do winning feature engineering and compete with peers in African countries. YEESI Lab believes not only in teaching AI models but also in training efficient, world-class, and accurate models.
yeesi lab pi invited for a public lecture at the Federal University of Lavras, Brazil
YEESI Lab PI was invited to present a video-conference public lecture to students and precision agriculture experts at the Federal University of Lavras, Brazil. He presented the role of Artificial Intelligence and Machine Learning in Digital Agriculture. He also presented the agenda that has been proposed in YEESI Lab to train youth on ML and AI. The main theme is how the youth can initiate their desire to learn ML/AI and utilize online learning platforms. He also talked about instructors recording videos and sharing talks to raise awareness and share experiences in Digital Agriculture. Also, He discussed the establishment of the start-ups in Digital Agriculture to boost the agenda in Africa and South America like how it is done in America, Europe, and Australia.
The PI of YEESI Lab was invited by Prof. Adão Felipe dos Santos, a Professor of Precision Agriculture
YEESI Lab participates in International Girls in ICT Day 2022
Science, technology, and innovation are the key drivers of our increasingly global and digital society. For girls and young women to thrive in science, technology, engineering, and mathematics (STEM) careers, they need safe and reliable access to digital tools. In line with the International Girls in ICT Day that will be celebrated on 28 April, YEESI Lab and the Tanzania Communication Regulatory Authority (TCRA) conducted a 1-day event with students from Kilakala secondary school on 9th April 2022 at SUA. The organisers of this event at SUA are Dr. Alcardo Alex Barakabitze and Prof. Camilius Sanga from YEESI Lab in collaboration with TCRA. The aim of this event was to encourage girls and young women to pursue science, technology, and engineering education and work in STEM careers. The main topic of the event focused on demonstrating to students from Kilakala secondary school the uses of ICTs and their impacts on the agriculture industry. Two female ICT scientists from SUA, Dr. Neema Sumari, Ms Joan Jonathan, and Dr. Neema Nicodemus presented their topics regarding “ICT for Future Smart World” and “Artificial intelligence (AI) and Machine learning (ML) in agriculture” respectively. Dr. Kadeghe Fue from YEESI Lab also presented smart technology and machine vision for precision agriculture where a robotic solution for cotton harvesting was demonstrated.
The TCRA at this event was represented by the Principal ICT officer and Eng. Aneth Kilaja.
REMOTE SENSING SEMINAR
You are invited to a scientific seminar on Machine Learning and Remote Sensing. It is sponsored by the research project: YEESI Lab
YEESI Lab PI talked to two AI-tech start-ups that have shown interest to work and collaborate with YEESI Lab and Sokoine University of Agriculture. He has agreed with the founders to establish official agreement that shall make SUA support the startups on computing nodes and ML tech collaborations.
YEESI Lab is a youth led initiative for youth of our great nation Tanzania. With the help of our partners, we are looking to organize and collaborate with AI-tech start-ups around the country and make positive collaborations.
14 March 2022
Being a learner through Problem based Learning
YEESI LAB ONLINE COURSES TO BOOST STUDENTS/TECHNOLOGISTS KNOWLEDGE ON MACHINE VISION HAVE BEEN LAUNCHED
PI, co-PI, and Instructors from YEESI Lab have won MACHINE LEARNING/VISION RELATED PROPOSALS IN THE SUA RESEARCH AND INNOVATION SUPPORT (SUARIS) second PHASE
Quad ai workstation arrived at sokoine university of agriculture
Our project lab received a high computing node from Lambda Labs on November, 4th, 2021. The master Quad AI workstation equipped with twin NVIDIA RTX A5000 with intel i9 18-cores processor running on massive 256GB RAM arrived in SUA's premises to support AI research efforts in Agriculture. This is the first modern GPU-installed node to have arrived at SUA. This server has been set to support YEESI Lab developers using JupyterHub server. It can be accessed on (locally) http://10.10.97.236/hub/login or (globally) http://220.127.116.11/hub/login
You are all welcome to explore AI work and support the state-of-the-art AI research in Agriculture.
Jupyterhub server and e-learning system set to implement ai in agriculture
We have configured the JupyterHub server to be shared by peers in our lab to train models. The server can be accessed on (locally) http://10.10.97.236/hub/login or (globally) http://18.104.22.168/hub/login
Also, the e-Learning Portal was deployed at http://22.214.171.124:8390/ to share materials and knowledge in AI.
Recently, the lab developed a comprehensive student-centered curriculum for machine vision. The curriculum features Problem-based Learning courses such as Problem-solving and Program Design with Python, Introduction to Digital Agriculture, Mobile Application Development, Machine Learning in Agriculture, Machine Vision in Agriculture, and Entrepreneurship for Artificial Intelligence that will empower the youth of Morogoro on next-generation AI research and development.