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This repository contains the complete codebase for the Lakeye project, an innovative autonomous submersible microscope designed for in-situ phytoplankton observations and imaging. The code includes modules for remote control via Telegram, sensor data management for temperature and humidity, LED illumination control, etc..

Home Page: https://www.instagram.com/lakeye_epfl/?hl=fr

Python 97.81% Shell 2.19%

lakeye-embeddedsystems's Introduction

Lakeye Project

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Overview

This is repository contains the code I implemented for the Lakeye project. The Lakeye project by a group of students of École Polytechnique Fédérale de Lausanne focuses on designing, prototyping, and business analysis of an autonomous submersible microscope named Lakeye. It aims to facilitate in-situ observations and imaging of phytoplankton, improving water quality monitoring. The team consists of Victor Michaud, Thomas Manteaux, Vincent Naayem, Benoît Pelisson, Marius Paganel, and Philippe Parisot, guided by team coach Samuel Benketaf and Professors Yves Bellouard & Edoardo Charbon.

LakEye on youtube

SnapSave.io-LakEye.video.Final-.1080p.mp4

Key Features

  • Autonomous Underwater Microscope: Designed to collect and transmit images, and analyze aquatic life in-situ.
  • Modularity and Energy Self-Sufficiency: Allows easy modifications and is powered by solar panels.
  • Innovative Design: Incorporates dark field illumination for enhanced imaging and contrast of nearly transparent objects.

Market and Unique Selling Points

  • Target Markets: Public institutions, private aquaculture professionals, scientific research, and NGOs.
  • Unique Aspects: Lakeye differentiates itself through its modularity and autonomy, offering a flexible and energy-efficient solution for water quality monitoring.

Technical Specifications

  • Structure: Modular with a waterproof shell, allowing for granular optical adjustments and easy component replacement.
  • Optical System: Dark field illumination with a resolution of 22.1 microns, and a 1.8X magnifying objective coupled with a Raspberry Pi HQ camera.
  • Electronics: Nano-computer for data management, temperature and humidity sensors, LED ring for illumination, and 4G connectivity for remote operation.

Project Management and Business Plan Aspects

  • Intellectual Property: Analysis of existing patents and strategies for unique IP development.
  • Pre-Business Plan: Market analysis, competitive positioning, commercialization strategy, organizational structure, and financial planning.
  • Project Management: Utilized tools like Work Breakdown Structure (WBS) and Gantt charts for efficient project execution.

Repository Code Files

Key components include:

  • telegram_interface.py: Manages the Telegram bot interface for remote control and monitoring of Lakeye.
  • sensor_dht.py: Handles temperature and humidity sensing.
  • led_ring.py: Controls the LED ring used for illumination.
  • db_manager.py: Manages database operations for storing image data.
  • cam_stream.py: Handles camera streaming functionality.

Conclusion

Lakeye project demonstrates an innovative approach to environmental monitoring, combining technical prowess with strategic market analysis and business planning. The project is set to evolve further, potentially expanding its impact in scientific research and public health sectors.

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