Data Processing for Utility Infrastructure

Our group aims to tackle the challenges faced in the utility/industrial/real estate infrastructure through statistical, Machine Learning and Deep Learning approaches with an emphasis to mitigate climate change. To this end, we focus on digitizing and integrating data from heterogenous sources, embedding knowledges and enable techniques that increase operational efficiency and reduce carbon emissions. We deal with time-series data (e.g., consumption data from smart meters), GIS data (e.g., network topology, geolocations of network components), SCADA data (network performance, e.g., pumps). Our current research revolves around database modelling, development of digital twin for utility networks (e.g., as a knowledge graph) as well as ML and DL algorithms for different applications such as load predictions, time-series clustering, anomaly detection/localization and data exploration.

Projects

UtilityTwin

Start: September 1, 2021

End: August 31, 2024

Description:

In the UtilityTwin research project, an intelligent digital twin for any energy or water supply network is to be researched and developed on the basis of adaptive high-resolution sensor data (down to the sub-second range) and machine learning techniques. Overall, the technology concepts BigData and AI are to be combined in an innovative way in this research project in order to make positive contributions to the implementation of the energy transition and to counteract climate change.

Participating Scientists

Adithya Ramachandran, M. Sc.

Phone number: +49 9131 85-27882
Email: adithya.ramachandran@fau.de
Website: https://lme.tf.fau.de/person/ramachandran/

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Siming Bayer, Dr. -Ing

Mobile phone: +4917622520695
Email: siming.bayer@fau.de
Website: https://lme.tf.fau.de/person/sbayer/

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Colloquium time table

Zoom Link

Thema: DPUI Colloq
Uhrzeit: 3.Feb. 2023 02:00 PM Oslo

Zoom-Meeting beitreten
https://fau.zoom.us/j/69883077724?pwd=K2ZMenZkM05SSm5TcDlKdi9iL2h1Zz09

Meeting-ID: 698 8307 7724
Kenncode: 911234
Schnelleinwahl mobil
496950500951,,69883077724#,,,,*911234# Deutschland
496950500952,,69883077724#,,,,*911234# Deutschland

Einwahl nach aktuellem Standort
49 69 5050 0951 Deutschland
49 69 5050 0952 Deutschland
49 695 050 2596 Deutschland
49 69 7104 9922 Deutschland
49 69 3807 9883 Deutschland
49 69 3807 9884 Deutschland
Meeting-ID: 698 8307 7724
Kenncode: 911234
Ortseinwahl suchen: https://fau.zoom.us/u/cbKt9aqBl

Über SIP beitreten
69883077724@fr.zmeu.us

Über H.323 beitreten
213.19.144.110 (Amsterdam
Niederlande)
213.244.140.110 (Deutschland)
Kenncode: 911234
Meeting-ID: 698 8307 7724

", "image": "", "name": "Journal Club", "url": "https://lme.tf.fau.de/events/journal-club-3/" }

February

Friday

Journal Club

Zoom

2:00 pm - 3:00 pm

View Detail

Bi-Weekly Colloq of DPUI group

Thema: DPUI Colloq
Uhrzeit: 17.Feb. 2023 01:00 PM Oslo
Jede Woche am Fr
17.Feb. 2023 01:00 PM
24.Feb. 2023 01:00 PM
3.März 2023 01:00 PM
10.März 2023 01:00 PM
17.März 2023 01:00 PM
24.März 2023 01:00 PM
31.März 2023 01:00 PM
7.Apr. 2023 01:00 PM
14.Apr. 2023 01:00 PM
21.Apr. 2023 01:00 PM
Laden Sie die folgenden iCalendar-Dateien (.ics) herunter und importieren Sie sie in Ihr Kalendersystem.
Wöchentlich: https://fau.zoom.us/meeting/u5EvdOqgrD0rEtzIwrJyGNIM8bs5H3DNXptQ/ics?icsToken=98tyKu-trDgpEtaTsRGPR_MMAIjCb_zzpiFcj7dHtQj3KTl0TCrbbuBRZ5osNPbo

Zoom-Meeting beitreten
https://fau.zoom.us/j/65233826188?pwd=ZkhqcHN2VWNCeTYxcUNVbklIS2VFZz09

Meeting-ID: 652 3382 6188
Kenncode: 546360
Schnelleinwahl mobil
+496950500951,,65233826188#,,,,*546360# Deutschland
+496950500952,,65233826188#,,,,*546360# Deutschland

Einwahl nach aktuellem Standort
+49 69 5050 0951 Deutschland
+49 69 5050 0952 Deutschland
+49 695 050 2596 Deutschland
+49 69 7104 9922 Deutschland
+49 69 3807 9883 Deutschland
+49 69 3807 9884 Deutschland
Meeting-ID: 652 3382 6188
Kenncode: 546360
Ortseinwahl suchen: https://fau.zoom.us/u/cbxoifntl3

Über SIP beitreten
65233826188@fr.zmeu.us

Über H.323 beitreten
213.19.144.110 (Amsterdam
Niederlande)
213.244.140.110 (Deutschland)
Kenncode: 546360
Meeting-ID: 652 3382 6188

", "image": "", "name": "DPUI Colloq", "url": "https://lme.tf.fau.de/events/dpui-colloq/" }

February

Friday

Data Processing for Utility Infrastructure

Fr. 9:00 -15:00

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