• AI Projects with practical Experience

Scrap it regularly in the business domain of Tourism

Scrap it regularly in the business domain of Tourism

Project Profile

Compensation of errors in signaling data by making the relevance evaluable with alterative measurement (Google waiting times). Born from the need of data acquisition, the approach to realize a data acquisition for Common Data /Frequent Data usage with simple means.

At a glance - essential project data

DurationFrom 5/1/2019 to 5/31/2019 with about 1 months of full engagement
Data and ToolsMarket - Tourism
Sources
 • Google Search API
 • Google Places
 • Scraping dynamically the requested 3000 Locations
 • Every new location is requested upon API Call
Integration • Runs on a Rasperry PI (Low Energy Consumption!)
 • Aggregates 3000 Location Data since 06/2019
 • Coverage of Locations Continuously providing a simple API for Customer Requests (CMS/Location Database)
AI Methods • Python (deep ?) tricks
 • ML and Statistics

Engagement Use-Case

Searching waiting times, opening hours for data mining to populate central systems.

Client motivation / Solution aims

  • Simple data mining for ML models to predict waiting times in POIs (as alternative for transaction data)

AI Approach

AI key technology used in our solutionStatistically enhancing of the Google API for standard usage
Solution ApproachML
Project ApproachSimply agile
Project TypeProject
ML Integration and ML Operations • Operation Integration
 • Rasperry PI

Insights and Details

Simple scrapping of commonly available information