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Maina Samuel

ML & AI Developer

Nairobi, Kenya

mainasamuel505@gmail.com

+254725680517


Skills

Python Programming

Artificial Intelligence

Machine Learning

Internet of Things


Languages

English

Swahili



Work Experience

Intern / Nairobi Bottlers Limited
Jan 2020 - Apr 2020

• Trained and worked on electrical and control motor circuits, automation technologies such as Siemens PLCs and industrial networking technologies such as ASiBus and Profibus.

• Actively involved in the operation, repair, preventive, and corrective maintenance activities such as breakdown and root course analysis of bottle filling equipment.

• Appreciated the use of sensors in temperature measurement, pressure measurement, level measurement, and object detection in automation.


Education

Dedan Kimathi University of Technology
May 2017 - Dec 2021

BSc. Electrical and Electronics Engineering


Thika High School
2013 - 2016

Graduated


Projects

Computer Pointer Controller
2020
Description

Demonstrates the ability to run multiple models on the OpenVINO toolkit on one edge device to control a computer pointer by staring at different locations on the screen. This project utilizes 4 different AI pretrained models to the face, facial landmarks, estimate the head position and also the gaze.

Here is the github repository for the project. Link

Use Cases

People Counter App at the Edge
2020
Description

This project involves first finding a useful person detection model and converting it to an Intermediate Representation for use with the Model Optimizer. Utilizing the OpenVINO Toolkit Inference Engine API and the person detection model to perform inference on an input video, and extract useful data concerning the count of people in the frame and how long they stay in the frame. Send this information over MQTT, as well as sending the output frame, in order to view it from a separate UI server over a network.

Here is the github repository for the project. Link

Use Cases

Smart Queuing System
2020

A system that can be used in three different scenarios that depict real-world problems based on different sectors where edge devices are typically deployed to manage queues. There are three scenarios that have been implemented in this project:

  • Scenario 1: Manufacturing Sector
  • Scenario 2: Retail Sector
  • Scenario 3: Transportation Sector
The performance of this system has been tested on different devices on the Intel DevCloud with the best performing device that fits a customer's budget and requirement being recommended.


Here is the github repository for the project. Link

Computer Pointer Controller
2020

Graduated