Combining IoT, Machine Learning and Data Science for AEC
Walid Sabra
Leading digital transformations as an Executive MBA & Enterprise Architect. Skilled in strategy, architecture, project mgmt, product mgmt, TOGAF, and IoT. Driving growth and improving operations through technology.
Introduction
The Internet of things (IoT) is now beyond connecting your fridge or microwave to your smart phone. Industries and firms can now benefit from it.
The Idea of having a small device (IoT Device) connected to a data source such as field progress photos (time-laps), equipment, weather sensors ...etc. and streaming this data to a Business Intelligence (BI) repository or staging database for data analysis and dash-boarding is what makes decision making more powerful and projects more controlled.
Machine Learning (ML) is the concept of mining data overtime and applying algorithms on this data to be more educated on data; based on the behaviors and the outcome of each data set and the relevant results of this data set.
whether its a supervised or unsupervised machine learning depending on the case and the data; the outcome will always magnificent as long as we have a pattern for the best results and you can always benchmark your production to the this pattern.
A good example for machine learning we all use on daily basis is Google search. every time you look for something on google; you're not only getting what you're looking for, you're also educating google search engine on what to show in future in case other users looking for the same thing. in this case the search engine would be the machine and you're teaching it every time you search for something.
With Data science, solutions developers and software vendors can apply algorithms derive the best of your data and present the outcome on easy to use dashboards and utilize the power of cloud .
Throughout this article I will try to explain the different components and technologies that can be used to apply these concepts.