We perform an analysis of public transport data from The Hague, the Netherlands, combined from three sources: static network information, automatic vehicles location and automated fare collection ...data. We highlight the effect of bunching swings, and show that this phenomenon can be extracted using unsupervised machine learning techniques, namely clustering. We also show the correlation between bunching rate and passenger load, and bunching probability patterns for working days and weekends. We present the approach for extracting isolated bunching swings formations (BSF) and show different cases of BSFs, some of which can persist for a considerable time. We applied our approach to the tram line 1 of The Hague, and computed and presented four different patterns of BSFs, which we name “high passenger load”, “whole route”, “evening, end of route”, “long duration”. We analyse each bunching swings formation type in detail.
By virtue of the steady societal shift to the use of smart technologies built on the increasingly popular smart grid framework, we have noticed an increase in the need to analyze household ...electricity consumption at the individual level. In order to work efficiently, these technologies rely on load forecasting to optimize operations that are related to energy consumption (such as household appliance scheduling). This paper proposes a novel load forecasting method that utilizes a clustering step prior to the forecasting step to group together days that exhibit similar energy consumption patterns. Following that, we attempt to classify new days into pre-generated clusters by making use of the available context information (day of the week, month, predicted weather). Finally, using available historical data (with regard to energy consumption) alongside meteorological and temporal variables, we train a CNN-LSTM model on a per-cluster basis that specializes in forecasting based on the energy profiles present within each cluster. This method leads to improvements in forecasting performance (upwards of a 10% increase in mean absolute percentage error scores) and provides us with the added benefit of being able to easily highlight and extract information that allows us to identify which external variables have an effect on the energy consumption of any individual household.
In addition to providing for a more reliable distribution infrastructure, the smart grid promises to give the end users better pricing and usage information. It is thus interesting for them to be ...ready to take advantage of features such as dynamic energy pricing and real-time choice of operators. In this work, we propose a system to monitor and control an office environment and to couple it with the smart grid. The idea is to schedule the operation of devices according to policies defined by the users, in order to minimize the cost of operation while leaving unaffected user comfort and productivity. The implementation of the system and its testing in a living lab environment show interesting economic savings of an average of about 35% and in some cases even overall energy savings in the order of 10% for a building equipped with renewable generation plants, and economic and energy savings of 20% and 10%, respectively, for a building without local renewable installations.
Understanding Travel Behavior through Travel Happiness Mantouka, Eleni G.; Vlahogianni, Eleni I.; Papacharalampous, Alexandros E. ...
Transportation research record,
04/2019, Letnik:
2673, Številka:
4
Journal Article
Recenzirano
Odprti dostop
The aim of this paper is to extend past research on travel behavior analysis by investigating travelers’ emotions and perceptions of the system’s performance. Perceived travel happiness as an ...extension of travel satisfaction is researched in the framework of the decision-making process during traveling. Socio-demographic, cognitive, and affective data were collected from a questionnaire survey that took place in Athens (Greece), the Netherlands, and Barcelona and Salamanca (Spain). A Bayesian network was developed to investigate the interrelations between travel happiness and parameters that affect travel behavior. Findings revealed that travel mode choice directly affects the level of happiness that a person experiences during everyday trips. Moreover, travel happiness is directly associated with the traveler’s perception of the occurrence of disruptions during everyday trips and the level of tolerance he/she has toward such disruptions. Results also indicated that further research should focus on understanding how the topology and performance of each country’s system affect travel-related choices. Finally, a discussion of the most significant results is provided.
To deal with the degraded performance of Global Navigation Satellite Systems (GNSS) in indoor environments, Indoor Positioning Systems (IPS) have been developed. The rapid proliferation of ...smartphones has led to many IPSs that utilize positioning technologies that are readily available on modern smartphones; including Bluetooth Low Energy (BLE).Using radio signals such as BLE in indoor environments comes with a number of challenges that can limit the reliability of the signal. In dealing with these challenges, most existing BLE-based IPSs introduce undesired drawbacks such as an extensive and fragile calibration phase, strict hardware requirements, and increases in the system's complexity. In this paper, an IPS is developed and evaluated that requires minimal setup for indoor environments and has a sufficiently low complexity to be run locally on a modern smartphone. An extensive exploration of the IPS' parameters was performed. The best performing parameter combinations resulted in a median positioning error of 1.48 ± 0.283 meters, while using the log-distance path loss model for distance estimation and Weighted Centroid Localization with a weight exponent be-tween 2.0 and 3.5 for position estimation.
Emerging data driven digital economy and Industry 4.0 transforms all sectors including industry, research and business. It requires new types of the general workforce and specialists that can ...effectively use digital and data technologies, variety of tools and global infrastructure services, and are capable for personal skills management and self-study. The paper provides an overview of the existing frameworks for competences, skills and qualifications that sets up a baseline for further research and definition of the skills for emerging data driven digital economy. The paper analyses the general profile of the modern agile data driven companies, their culture and required competences. The paper shares the experience of introducing professional and 21 st Century skills in the bachelor and master courses. The project based learning model is proven to be effective in this cases combining the student initiative and self-organisation given the well defined course objectives and reporting requirements.
This paper investigates how to complement Complex Event Processing (CEP) with dynamic quality monitoring mechanisms and support the dynamic integration of suitable sensory data sources. In the ...proposed approach, queries to detect complex events are annotated with consumer-definable quality policies that are evaluated and used to autonomously assign (or even configure) suitable data sources of the sensing infrastructure. We present and study different forms of expressing quality policies and explore how they affect the process of quality monitoring including different modes of assessing and applying quality-related adaptations. A performance study in an IoT scenario shows that the proposed mechanisms in supporting quality policy monitoring and adaptively selecting suitable data sources succeed in enhancing the acquired quality of results while fulfilling consumers' quality requirements. We show that the quality-based selection of sensor sources also extends the network's lifetime by optimizing the data sources' energy consumption.
Human-Assisted Rule Satisfaction in Partially Observable Environments Degeler, Viktoriya; Curry, Edward
2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops,
12/2014
Conference Proceeding
Many lightweight installations of smart environment systems do not have complex and expensive sensing and actuating capabilities, leaving parts of the environment unobservable to the system. This ...limits reasoning and decision making complexity of such systems. A decision support system that can collaborate with human users alleviates this problem by asking users to provide missing pieces of information or to perform actuations of which the system itself is incapable. In this paper we present a smart system that uses declarative rules to describe the expected behavior of the environment. In any situation the system aims to satisfy the rules by finding the actions to transform the environment state to conform to existing restrictions. The system asks users to provide missing information that is relevant to the final decision or to perform required actions. A decision tree is constructed, which defines the actions depending on user's answers. The system constructs it in such a way to minimize the expected efforts of users. We present two ways of constructing such a decision tree. One uses backtracking for optimal results, and the other uses a heuristic approach for faster decision tree creation. We show that the relatively small drop in efficiency allows most smart environments to use the fast heuristic algorithm for decision tree construction.
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