Dear Prospective Student,
Thank you for your interest in the course Geo Sensor Networks and the Internet of Things.
The registration period for the course begins on 15.03.2023. From this date, the course will be visible on TUMOnline.
There are limited enrolment seats available, and thus we strongly encourage you to apply as early as possible.
We are looking forward to seeing you in the summer semester.
Marking of the Geo Sensor Networks and the Internet of Things (ED110027 and ED110046) has been completed, and the grades published. If you would like a review of the grading, please send us a request.
Thank you all for your active participation, and we wish you all the best.
A quick reminder to the students taking the ED110046: (6 ECTS) module, the paper review submission deadline is the 1st of September, 2022.
Please upload your paper review in either PDF or DOC format to this link Upload Link. The file name should be in the following format: lastname_firstname.
To the students taking the ED110046: "Internet of Things for the Built Environment" for Environmental Engineering (6 ECTS) module, we have selected research papers for you to review. Each student will receive the allocated research paper in their Slack inbox.
Please find the paper review guidelines under the following link Paper review guidelines.
I put together a page on how to handle library issues on Arduino: Troubleshooting Arduino IDE
Hey all, earlier today I released some important changes to our IoT infrastructure. You can now map location information of your devices using the Cayenne payload GPS field. Checkout the updated FROST - Tutorial to learn about the latest changes to the mapping document. Moreover, there are some new error messages that make it easier to find what's wrong with the mappings. They are described in Testing LoRaWAN connections.
The exam registration is now open. For our course, Geo Sensor Networks and the Internet of Things, there are two modules available as follows:
- ED110027: "Geo Sensor Networks and the Internet of Things" for Geodesy and Geoinformation (5 ECTS).
- ED110046: "Internet of Things for the Built Environment" for Environmental Engineering (6 ECTS).
Hey all, the videos of yesterday's lecture are now available in Course material.
the updated version of the slides is now available in Course material.
The videos of the theory session and exercise from yesterday are online now in Course material.
Hey all, the slides of the first lecture are now available in Course material.
I forgot to mention where you can find the join link for Slack. All you need is in Course communication (Zoom, Slack).
Please join as soon as possible and don't hesitate to ask questions if you have some!
please make sure to register for the exam of this course and to complete your wiki documentation in time.
All required information is here: Organization#RegistrationandDeadlines
here is the tutorial on how to get your data to the FROST-Server I promised yesterday. Take a look and contact us if you need help.
FROST - Tutorial
I am out of office until next Tuesday and will not be able to reply to you until then.
I just setup the services for the course. You can find them here:
LoraWAN Package Listing
Incoming TTN and SWM packages are now listed here:https://gi3.gis.lrg.tum.de/nodered/ui/
The FROST-Server is the IoT-Platform where all your sensor data from your nodes will be stored. We will show you next week how to brin gyour data there. For now, checkout the FROST Server page to query some data from out testing nodes.
- FROST-Server: https://gi3.gis.lrg.tum.de/frost/v1.1
Grafana is the tool we are going to use for data visualization. Teh login below provides you with edit rights. Just try to create a dashboard of your own. No worries, there is nothing you can destroy here, just give it a try. You can learn more about that here: https://grafana.com/docs/features/panels/graph/
The time-series values stored in the FROST Server can be visualized by an Open Source Dashboard application Grafana. Grafana has a plug-in called LinkSmart-SensorThings-Datasource, which allows to query and visualize the sensor observations from arbitrary SensorThings API services.
- Grafana: https://gi3.gis.lrg.tum.de/grafana
user: gi3-student, password: geoSensorWeb2020!
- Demo Dashboard: https://gi3.gis.lrg.tum.de/grafana/d/BgUQkCmGz/gi3-testnodes?orgId=1&refresh=1m