Personal details

Miguel S. - Remote back-end developer

Miguel S.

Senior Software Engineer
Based in: 🇧🇪 Belgium
Timezone: Brussels (UTC+2)

Summary

During my daily work activity I do Research , Prototype and Deployment of Smart AI enabled Technology Solutions. I also Advise and Mentor technology solutions to individuals and organizations (enterprises and institutions).

I prototyped and about to publish the 3rd scientific paper on self sensing carbon fiber composite materials for active structural monitoring , and for the past 4 months now, I've been prototyping smart DAQ devices to connect such materials to and edge server. The main objective, give life to a structure, by seamlessly integrating any structural element into a remote, live active (or passive) monitoring network with usage of artificial intelligence technologies all together.

Some Metrics

■ 1 Digital Transformation in the Laboratory of construction and building materials at University of Minho, Portugal (2005/09)
■ 3 Digital Transformations at start-up enterprises (2007/8; 2014/2016; 2018/20)
■ 10 M.V.P. prototypes licensed © under open source and open data standards:
░ ¤ Sitebuilder CMS (1999/09)
░ ¤ Self-sensor carbon based composites (2005/07)
░ ¤ Common injection rail for Automotive LPG systems (2014/16)
░ ¤ Custom multi environment software and hardware electronics solutions for remote with real-time data collection and management of construction site logistics and HR (2018/20)
░ ¤ 6 PCB Prototyping (see GitHub) for
░ ░ ¤ home automation
░ ░ ¤ Industrial automation
░ ░ ¤DAQ smart devices (LDAD)

With nearly 30 years of programming experience , I've coded on pretty much all the languages there is to code. If you don't find your preferred stack do be alarmed i can add value to your project with the stack of your choice.

Work Experience

Senior Technology Advisor
Aluminios Nelugo Lda | Dec 2021 - Present
Android
C++
Mentoring
Technical Writing
Pcb prototyping
Alumínios Nelugo, Lda is looking to take the next step and adopt smart simple technologies in their work methodologies of delivering aluminium frame solutions to clients in the construction sector with real-time updates. The proposed solution is based in Open Data and open source guidelines. If you're interested and want to learn more, you can find an early draft of the proposed digital transformation solutions here (doc. in Portuguese): https://migueltomas.substack.com/p/digital-transformation-proposal-1st
Technology Specialist
Universidade Federal de Santa Maria | Jan 2021 - Present
Android
C++
Transfer learning
Edge Computing
Pcb prototyping
Advisory in the following Technologies: Research Data Management, Open Data, Open Source, Edge Computing, Transfer Learning , Live Data Acquisition, Artificial Intelligence, Machine Learning Implementation of smart DAQ technologies in a PhD program. Teaching & training for : - remote data acquisition of experimental data - remote work experimental data - time dependent analysis of experimental data with machine learning open source tools such as image analysis for pattern detection and time series analysis of experimental data

Education

KTH
master course・Artificial Intelligence in Society
Mar 2022 - Jul 2022
Universidad Alcala
Master's degree・Artificial Intelligence and Machine Learning
Mar 2020 - Mar 2022

Personal Projects

Construction Site LogisticsIconOpenNewWindows
2020
PHP
Android
C#
MySQL
RESTful API
implemented successfully a work methodology to all 70+ construction workers and move forward the enterprise by enabling delivery of work and communication in real-time at each construction site while managing all logistics aspects of construction works through a cloud logistics platform, also planned from the start by me, developed and coded. Currently consists of 2 android Apps, 1 windows desktop Apps in .NET Core. All connecting to a cloud server API and where data is stored and shared among devices encrypted using current encryption standards.
LDAD - live data acquisition deviceIconOpenNewWindows
2021
PHP
Android
C++
MySQL
KiCad
IoT on Edge Computing / Transfer Learning Since last June 2021, amid Covid-19, I’ve been designing a live data acquisition device (LDAD) for monitoring of sensor data. It uses an Arduino board coupled with a custom PCB board, and commercially available Arduino shields. (see my activity posts here on LinkedIn and also on Twitter @AeonLabsS) The first version of the LDAD is targeting monitoring of fresh concrete hardening by measuring its core temperature using a type K thermocouple, the environment temperature and relative humidity (SHT31 shield) allowing the calculation of concrete maturity at any given day. Collected data is stored locally on a SPI Flash memory chip (W25Q128) for later synchronization with the local network or connected device. The LDAD uses RFID NFC technology for fast identification and connection to nearby authorized devices, such as smartphones, tablets or any other that uses Bluetooth BLE or WiFi technologies. In parallel is also being developed custom software applications for handling and managing collected data from devices compatible with LDAD and in accordance to the latest guidelines on Open Data available at the European commission website and also following the latest guidelines available on open-source development and maintenance. See my activity posts here on LinkedIn and also on Twitter @AeonLabsS for a preview of what i am able to deliver in a more visual manner.

Certifications & Awards

Sci. Publication: Implementation of Real-Time Logistics with Transfer Learning at a Small Start-Up Enterprise in the Construction Sector
available as a preprint at SSNR : https://papers.ssrn.com/abstract=4027845 | Feb 2022
Sci. Publication: A Deep Neural Network for Electrical Resistance Calibration of Self-Sensing Carbon Fiber Polymer Composites on Edge Computing Monitoring Solutions
available as a preprint SSRN: https://papers.ssrn.com/abstract=4027801 | Jan 2022