Ekani Louis

Ekani Louis

Ekani Louis, born in 1994 in the city of Yaoundé the capital of Cameroon, he obtained a BACCALAUREA series D in 2012 then continued his studies at the graduate level at the University Institute of the Coast in engineering cycle where he obtained his engineering diploma in embedded system and mobile robotics 5 years later.

He started his professional career at Alpha Inter service as a developer then left the company early enough to put his know-how as a robotics engineer with Will&Brothers as part of the DroneAfrica project (now Algo Drone). He worked there as a consultant and then as a project manager. Nurturing other ambitions, he created House Innovation a structure dedicated to technological innovation with 3 of his former classmates.

1. Can you start by telling us more about how you got into AI and what about it ignites your interest?

I didn’t really know what AI was until my second year of engineering school 6 years ago. I used to love programming and I’m a fan of science fiction movies. Then one evening I saw one of my favorite movies “Iron Man ” with his IA Jarvis again. This night, I started doing research on the Internet and realized that beyond science fiction it was possible to give intelligence to a machine and it became a passion for me given the countless possibilities that this reflected.

2. In a nut shell, what is ‘deep learning’? How does this differ from simpler forms of ‘AI’? How important is good data to training an effective AI?

Deep learning to make it simple is a learning done on the basis of large data sets unlike algorithms such as SVM. It is characterized by a succession of layers of neurons. A neuron is indeed a processing point which in a learning process will allow to determine a specifics characteristics (weights) to a data and in an analysis process will serve as a switch (thanks to an activation function) to form with the other neurons of the network a schema corresponding to an analysis result on the basis of the pre-trained data.

Artificial intelligence is like a child being educated. If you tell a child throughout the year that 1+1= 11 then, expect that when you ask him or her the question: what is equal to 1+1? he answers 11. Hence the need to provide correct data to the AI for training.

3. What is House Innovation SARL’s unique approach to tackling the complexities of training AI?

I don’t know if we can say that this is a unique approach. But we try to put things in context by using data that correspond to our reality and even if today computing power is what we lack most, we take a lot of time and pleasure to train our AIs and correct the errors observed in the test phases.

4. What are the implications for industry making increasing use of AI trained IoT devices and machines?

There are positive aspects to the use of these technologies because they allow absolute control and short, medium and long-term forecasts to be made, to name but a few, unfortunately there is always a setback. Some will say that machines are increasingly taking the place of man in industry, which is true, but it must also be admitted that these technologies also create new jobs, I often like to take the example of drones, which today are revolutionizing quite a few sectors. Today, the profession of drone pilot does exist, which was not the case before.

5. What are the potential applications, and problems AI such as this can solve? How has House Innovation SARL’s AI training specifically been applied to the field of UAVs?

There are many applications in the health field, for example, it is possible to identify cellular anomalies using data collected with a microscope, which can be done in a few seconds.  We are currently working on this theme with a brilliant nurse researcher named Boumtje Véronique. In the agricultural sector we are now able to detect diseases on plants with intelligent cameras and to know what conditions (temperature, pressure, humidity…) have favoured the development of these diseases with the different sensors installed in the field as part of our AllGreen project.  We are in the testing phase on greenhouse crops with the collaboration of Green House Venture and Robot Save.

In the field of drones, we collaborated with Algo Drone to set up the Cyclop project, the main aim of which is to make drones intelligent. The project not being completed, I can’t tell you more.

6. If you could say one thing to a potential customer to convince them of how your company’s technology will help them streamline workflow and data processing, what would it be?

I would say, “Your business is working well, but do you know that it could be even better? Control, speed, efficiency, accuracy and prediction are our guarantees”

7. What’s in the future for House Innovation SARL?

House Innovation is a technological innovation cluster. Our biggest challenge today is to find investment in order to bring our projects to fruition. On the one hand, we want to share our know-how with the world, which means that the company must grow and become a multinational. And on the other hand we want to boost the African technological ecosystem we are also a member of an Afrobot association whose aim is to train young people in new technologies on a voluntary basis. 

Perspectives on UAS in the next years

We recently started in entertainment with the manufacture of the very first model of racing drone in Central Africa we are currently looking for funds to open a large high-tech leisure center where we can organize drone racing competitions and why not participate in international tournaments. We are convinced that UAV races will become a real sport in the same way as car or motorcycle races. In the agricultural sector, our research is continuing with a view to setting up disease detection drones on plants.

The biggest challenges

The biggest challenge facing us is the acquisition of equipment in a very poorly industrialized ecosystem, it is very difficult to develop cutting-edge technologies.  In addition, deployment on the local market always requires a major phase of education when it comes to technological innovation in order to attract as many people as possible.


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