@techreport{AuerBenekenBrummeretal.2017, author = {Auer, Veronika and Beneken, Gerd and Brummer, Benjamin and Ch{\^a}teauvieux-Hellwig, Camille and Engler, Benjamin and Gilly, Alexander and Hagl, Rainer and Hummel, Felix and Hummel, Sabine and Karlinger, Peter and Knorr, Ludwig and K{\"o}ster, Heinrich and Kucich, Martin and Mecking, Simon and Rabold, Andreas and Sandor, Viktor and Schalk, Daniel and Schanda, Ulrich and Schemme, Michael and Schiffner, Ivonne and Schmidt, Jochen and Schugmann, Reinhard and Seidlmeier, Heinrich and Sigg, Ferdinand and Stauss, Kilian and Sussmann, Monika and Wellisch, Ulrich and Wenninger, Marc and Wittmann, Josef and Zscheile, Matthias}, title = {Jahresbericht 2016, Forschung - Entwicklung - Innovation}, organization = {Hochschule Rosenheim}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-12282}, pages = {68}, year = {2017}, abstract = {Mit dem j{\"a}hrlich erscheinenden Forschungsbericht m{\"o}chte die Hochschule Rosenheim einen Einblick in ihre vielf{\"a}ltigen Projekte und Aktivit{\"a}ten der angewandten Forschung und Entwicklung geben. Im Jahresbericht 2016 wird {\"u}ber Vorhaben im Jahr 2016 berichtet.}, language = {de} } @techreport{AckermannAngermeierAueretal.2014, author = {Ackermann, Timo and Angermeier, Martin and Auer, Veronika and Beneken, Gerd and Bernhardt, Andreas and Botsch, Rafael and B{\"u}cker, Dominikus and Hager, Ralf and Hauck-Bauer, Eva and Heigl, Martin and Hirschm{\"u}ller, Sebastian and H{\"o}llm{\"u}ller, Janett and Karlinger, Peter and K{\"o}ster, Heinrich and Krause, Harald and Kucich, Martin and Matthias, Kira and Patzl, Victoria and Pl{\"o}nnigs, Ren{\´e} and Posch, Georg and Schanda, Ulrich and Scheerer, Josua and Schlecht, Johannes and Schmidt, Jochen and Stichler, Markus and Uhl, Cornelius and Viehhauser, Peter and Weber, Gabriel and Wolf, Christopher and Zagler, Stefan and Zentgraf, Peter}, title = {Forschungsbericht 2013}, organization = {Hochschule Rosenheim}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-12324}, pages = {56}, year = {2014}, abstract = {Mit dem j{\"a}hrlich erscheinenden Forschungsbericht m{\"o}chte die Hochschule Rosenheim einen Einblick in ihre vielf{\"a}ltigen Projekte und Aktivit{\"a}ten der angewandten Forschung und Entwicklung geben. Im Forschungsbericht 2013 wird {\"u}ber Vorhaben im Jahr 2013 berichtet.}, language = {de} } @article{WenningerBayerlSchmidtetal.2019, author = {Wenninger, Marc and Bayerl, Sebastian P. and Schmidt, Jochen and Riedhammer, Korbinian}, title = {Timage - A Robust Time Series Classification Pipeline}, series = {Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science}, volume = {11730}, journal = {Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science}, publisher = {Springer}, address = {Cham}, year = {2019}, abstract = {Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrence Plots. In order to utilize the research done in the area of image classification, where Deep Neural Networks have achieved very good results, we use a Residual Neural Networks architecture known as ResNet. As preprocessing of time series is a major part of every time series classification pipeline, the method proposed simplifies this step and requires only few parameters. For the first time we propose a method for multi time series classification: Training a single network to classify all datasets in the archive with one network. We are among the first to evaluate the method on the latest 2018 release of the UCR archive, a well established time series classification benchmarking dataset.}, language = {en} } @article{WenningerStecherSchmidt2019, author = {Wenninger, Marc and Stecher, Dominik and Schmidt, Jochen}, title = {SVM-Based Segmentation of Home Appliance Energy Measurements}, series = {Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019}, journal = {Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019}, pages = {1666 -- 1670}, year = {2019}, abstract = {Generating a more detailed understanding of domestic electricity demand is a major topic for energy suppliers and householders in times of climate change. Over the years there have been many studies on consumption feedback systems to inform householders, disaggregation algorithms for Non-Intrusive-Load-Monitoring (NILM), Real-Time-Pricing (RTP) to promote supply aware behavior through monetary incentives and appliance usage prediction algorithms. While these studies are vital steps towards energy awareness, one of the most fundamental challenges has not yet been tackled: Automated detection of start and stop of usage cycles of household appliances. We argue that most research efforts in this area will benefit from a reliable segmentation method to provide accurate usage information. We propose a SVM-based segmentation method for home appliances such as dishwashers and washing machines. The method is evaluated using manually annotated electricity measurements of five different appliances recorded over two years in multiple households.}, language = {en} } @book{Schmidt2019, author = {Schmidt, Jochen}, title = {Grundkurs Informatik - Das {\"U}bungsbuch: 148 Aufgaben mit L{\"o}sungen}, edition = {1}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3658259440}, publisher = {Technische Hochschule Rosenheim}, pages = {196}, year = {2019}, language = {de} } @book{BenekenErnstSchmidt2015, author = {Beneken, Gerd and Ernst, H. and Schmidt, Jochen}, title = {Grundkurs Informatik: Grundlagen und Konzepte f{\"u}r die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einf{\"u}hrung (Auflage von 2015)}, publisher = {Springer Vieweg}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2015}, abstract = {Das Buch bietet eine umfassende und praxisorientierte Einf{\"u}hrung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenh{\"a}nge, die dar{\"u}ber hinausgehen und macht sie verst{\"a}ndlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz f{\"u}r die praktische Anwendung. Praxisnah und aktuell werden die Inhalte f{\"u}r Studierende der Informatik und verwandter Studieng{\"a}nge sowie f{\"u}r im Beruf stehende Praktiker vermittelt. Die vorliegende f{\"u}nfte Auflage wurde grundlegend {\"u}berarbeitet und aktualisiert.}, language = {de} } @inproceedings{WenningerSchmidtGoeller2017, author = {Wenninger, Marc and Schmidt, Jochen and Goeller, Toni}, title = {Appliance Usage Prediction for the Smart Home with an Application to Energy Demand Side Management - And Why Accuracy is not a Good Performance Metric for this Problem.}, series = {6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)}, booktitle = {6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)}, year = {2017}, abstract = {Shifting energy peak load is a subject that plays a huge role in the currently changing energy market, where renewable energy sources no longer produce the exact amount of energy demanded. Matching demand to supply requires behavior Changes on the customerside, which can be achieved by incentives suchas Real-Time-Pricing (RTP). Various studies show that such incentives cannot be utilized without a complexity reduction, e.g., by smart home automation systems that inform the customer about possible savings or automatically schedule appliances to off-peak load phases. We propose a probabilistic appliance usage prediction based on historical energy data that can be used to identify the times of day where an appliance will be used and therefore make load shift recommendations that suite the customer's usage profile. A huge issue is how to provide a valid performance evaluation for this particular problem. We will argue why the commonly used accuracy metric is not suitable, and suggest to use other metrics like the area under the Receiver Operating Characteristic (ROC) curve, Matthews Correlation Coefficient (MCC) or F1-Score instead.}, language = {en} } @inproceedings{GoellerWenningerSchmidt2018, author = {Goeller, Toni and Wenninger, Marc and Schmidt, Jochen}, title = {Towards Cost-Effective Utility Business Models - Selecting a Communication Architecture for the Rollout of New Smart Energy Services}, series = {Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS}, booktitle = {Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS}, publisher = {SciTePress}, isbn = {978-989-758-292-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-8332}, pages = {231 -- 237}, year = {2018}, abstract = {The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example.}, language = {en} } @book{ErnstSchmidtBeneken2016, author = {Ernst, H. and Schmidt, Jochen and Beneken, Gerd}, title = {Grundkurs Informatik: Grundlagen und Konzepte f{\"u}r die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einf{\"u}hrung}, publisher = {Springer Vieweg}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2016}, abstract = {Zahlensysteme und bin{\"a}re Arithmetik Nachricht und Information Codierung und Datenkompression Verschl{\"u}sselung Schaltalgebra, Schaltnetze und Elemente der Computerhardware Rechnerarchitekturen Rechnernetze Betriebssysteme Datenbanken Automatentheorie und formale Sprachen Berechenbarkeit und Komplexit{\"a}t Suchen und Sortieren B{\"a}ume und Graphen prozedurale und objektorientierte Programmierung (C und Java) Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) Software-Engineering}, language = {de} } @inproceedings{ZengerSchmidtKroedel2013, author = {Zenger, A. and Schmidt, Jochen and Kr{\"o}del, M.}, title = {Towards the Intelligent Home: Using Reinforcement-Learning for Optimal Heating Control}, series = {Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence}, booktitle = {Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence}, publisher = {Springer}, year = {2013}, abstract = {We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method.}, language = {en} }