Portfolio
Here is a selection of the project we realized in the last months. Please click on the icons to see the product in action or a detail documentation (Note that these apps are just simplified copies of the original system).
Machine Learning
- Client: IoT Company
- Problem: Sensor Data Quality Checks
We used Machine Learnig to decide if sensor data are true readings or sensor errors. Main challenge was the sparse error data. We used Data Centric AI to solve the problem. Includes Whatsapp alerts when errors detected.
Agronomic App Dr. Uva
- Client: Embrapa Uva e Vinho
- Problem: Plant desease models as service
We developed a agronomic app with geospatial capabilites to integrate Emprapa's plant desease models and provide them as a service to farmers. It also provides includes GIS functions and GIS-AI applications.
Automatic Agronomic Reports
- Client: Service Company
- Problem: PDF Reports by Email
We developed an automatic system which integrates APIs, analyzes GIS data, creates customized PDF reports and sends them to clients. It includes R-Shiny App to manage sendings.
Deep Work Planner
- Client: For own use
- Problem: App to plan Deep Work
We developed a R-Shiny app, which helps to plan the quarterly, weekly and daily tasks according to the Deep Work method. Start with quarterly and weekly goals and break them down to daily time blocks for uninterrupted focus.
Soil Lab ERP
- Client: Soil Lab Service
- Problem: ERP to manage Lab workflow
We developed a R-Shiny app, which serves as an ERP to manage the entire workflow of the lab, from sample collection to analysis to invoicing to result communication. It include GIS mapping for the samples.
Media & Packages
R-Shiny Conference 2022
Michael's Shows R-Shiny App he developed. App includes comprehensive Geospacial functions and a DB connection.
Low-Code Tool
Michael developed low-code extension for R-Shiny. It allows to create new Apps in a very efficient way. Here a beta version.
About Michael
Michael is an Engineer and a Data Scientist graduated from the Massachusetts Institute of Technology. He looks back to a carrier in Engineering, R&D, Business Development and Management at different multinational technology companies, including in Schneider Electric. Michael is one of the leading R and R-Shiny Experts.
MIT Data Scientist & R/R-Shiny Developer
- Age: 40
- City: Bern, Switzerland
- Studied: Engineering, Data Science
- Degree: Master
- University: Massachusetts Institute of Technology
- Main Employments: Schneider Electric, Pessl Instruments, own Data Science Start-up
- Top Expertise: R, R-Shiny, Data Science, Machine Learning, GIS, AI
Skills
Better than most: I combine deep data science knowledge and practical R-Shiny expertise, which means I am very efficient in setting up entrepreise level Web-Apps to solve urgent data problems.
About Nilo
Nilo is a Brazilian engineer with focus on cloud deployment solutions and software development. His expertise is in DevOps, Cloud computing, infrastructure and project management. Nilo’s strength is his methodical work approach, his critical thinking and his project management skills.
DevOps Engineer and Cloud Infrastructure specialist.
- Age: 30
- City: Ponta Grossa, Brazil
- Studied: Engineering, Cloud Computing, Agribusiness
- Degree: Master
- University: UEPG - Universidade Estadual de Ponta Grossa
- Carreer: R&D, Product Engineer, DevOps Engineer
- Past Employers: EATON, Tibasoy
- Top Expertise: R, R-Shiny, AWS, DevOps, Python, Terraform
Skills
Testimonials
Luciano Loman
CEO Metos Brazil
Michael developed a fully integrated automatic PDF report sender, including API connection, Geospatial function, pdf generator and automatic E-mail sending. This tool is an important part for Metos Brazil's customer digital services.
Rodrigo
Agronomist & Owner Soil Lab
Michael developed an integrated Web App including Geospatial functions, which helps my lab to automate the entire workflow, from soil collection through result communication.
Anomymous
Maintenance Responsible at Metos Brazil
Michael came up with a very creative Machine Learning solution to automatically filter all our IoT sensor Data for potential sensor errors. This solutions saves us countless hours of time.
Marcos Botton
Head Techology Transfer, Embrapa Brazil
Michael developed a complete Digital Agriculture Web App for the Wine Grape Industry in South Brazil, though which Embrapa provides its Plant Disease Models as a service.
Contact
Location:
3048 Bern, Switzerland
Email:
michael@aliacon.com.br
Whatsapp:
+55 11 97401 0846