Ngesa Naphtally Marvin, Dedan Kimathi University of Technology

Hyacinth Monitor

Intel® AI DevCon

Factors that affect the movements of these weeds are used as training data set. These

factors/features include: wind direction & speed from the Wind forecast map Kenya and satellite

images.

The training data is then prepared and AlexNet, an image classification topology is then used to

classify the images. When using the Intel deep learning training tool, usually Intel® Distribution

for Caffe runs underneath.

ConclusionsI believe training and prediction algorithms can predict the exact location of water hyacinth in Lake Victoria. The model gradually learns the relationship between features (images, wind

direction & speed) and label.

The prediction algorithm will then use the trained model to predict the exact location based on new

data. When the location and movement trend of these weeds can be predicted, the local authorities can

then eradicate them.

AcknowledgmentsSincerest gratitude to Intel for their efforts in

providing great AI tools such as Intel Deep Learning SDK.

Lake Victoria, Africa’s largest fresh water body provides a lot of economic benefit to the local

community surrounding it. People fish and move around the lake with boats. In recent years, Water

hyacinth has become a major invasive plant species and it has negatively affected the local

ecosystems.

The weed blocks boats thus immediately affecting transportation, fishing and tourism activities.

The weeds also creates excellent breeding sites for mosquitoes and other insects. This results into

increase of diseases such as skin rash, cough, malaria, encephalitis, gastro-intestinal

disorders, and bilharzia/schistosomiasis.

Water supply is also affected as intake works and the irrigation canals are clogged and their

hydraulic efficiency is drastically reduced. When the supply intakes for the hydroelectric plant are blocked, electrical power supply is interrupted.

Intel Technology UsedIntel® Deep Learning Training Tool, Intel®

Distribution for Caffe*

Several efforts have been made by different parties to eradicate the weed, despite this, the weed continues to expand itself year after year.

To eradicate the weed, I believe that we should monitor its sources, how it spreads and its

movement in the lake. With better data about the location of the weed, we can help different

organizations and local stakeholders, predict its next destination. eradicate it.

.