Matthias Budde

Karlsruhe Institute of Technology | KIT · Institute of Telematics

T he interdisciplinary „Smart Air Quality Network" (SmartAOnet) project provides an overall system for recording, visualising and predicting the spatial distribution of air pollutant concentrations in urban atmospheres. Within more than three years SmartAOnet aimed to implement an inexpensive measurement network, which is transferable to other citi...

Urban air quality is an important problem of our time. Due to their high costs and therefore low spacial density, high precision monitoring stations cannot capture the temporal and spatial dynamics in the urban atmosphere, low-cost sensors must be used to setup dense measurement grids. However, low-cost sensors are imprecise, biased and susceptible...

The increasing availability of low-cost air quality sensors has led to novel sensing approaches. Distributed networks of low-cost sensors, together with data fusion and analytics, have enabled unprecedented, spatiotemporal resolution when observing the urban atmosphere. Several projects have demonstrated the potential of different approaches for hi...

Creating a public understanding of the dynamics of a pandemic, such as COVID-19, is vital for introducing restrictive regulations. Gathering diverse data responsibly and sharing it with experts and citizens in a timely manner is challenging. This article reviews methodologies of COVID-19 dashboard design and discusses both technical and non-technic...

Modern mobile phones are equipped with many sensors, which can increasingly be used to sense various environmental phenomena. In particular, mobile sensing has enabled crowdsourced data collection at an unprecedented scale. However, as laypersons are involved in this, concerns regarding the data quality arise. This work explores the gamification of...

Die naive Fusion von Messdaten unbekannter Qualität führt häufig zu keiner signifikanten Verbesserung von Vorhersagemodellen. Stochastische Regressionsmodelle bieten hier einen interessanten Ansatz, der es erlaubt, komplexe Zusammenhänge in vergangenen Daten zu erkennen, diese auf zukünftige Daten zu übertragen und somit Vorhersagen zu verbessern....

Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measurements, and inexpensive sensors do not meet accuracy demands. As a step towards filling this gap, we...

In Particulate Matter (PM) monitoring, current laser scattering low-cost sensor generations exhibit better stability than early sensor generations and feature internal digital processing to achieve more accurate results. As a representative of this class of sensors, we examine the popular SDS011 PM sensor. Previous work about co-location measuremen...

Sleep breathing disorder is a serious threat to a large share of the population. This paper presents a low-cost, tiny sensor system based on Volatile Organic Component (VOC) sensing for the detection of sleep apnea/hypopnea. We present two designs, discuss wearability aspects and show that the sensor works similar to gold standard Polysomnography (...

Human Activity Recognition (HAR) with body-worn sensors has been studied intensively in the past decade. Existing approaches typically rely on data from inertial sensors. This paper explores the potential of using point cloud data gathered from wearable depth cameras for on-body activity recognition. We discuss effects of different granularity in t...

The rise of the smartphone opens up new possibilities for researchers to observe users in everyday life situations. Researchers from diverse disciplines use in-field studies to gain new insights into user behavior and experiences. However, the collected datasets are mostly not available to the public and thus results are neither falsifiable nor rep...

Classic measurement grids with their static and expensive infrastructure are unfit to realize modern air quality monitoring needs, such as source appointment, pollution tracking or the assessment of personal exposure. Fine grained air quality assessment (both in time and space) is the future. Different approaches, ranging from measurement with low-...

The collection of human contributions through mobile devices is increasingly common across a range of methodologies. However, possible quality issues of these contributions are often overlooked. As the quality of human data has a direct impact on study reliability, more should be done to improve the accuracy of these contributions. We identify and...

The SmartAQnet research project is investigating a smart way of determining the spatial distribution of fine dust, prototyped at a demonstration site in Augsburg, Germany. The research approach is the collection of different qualities of fine dust measurement data and its combination with remote sensing data. Measured fine dust data can be fed into...

In Particulate Matter (PM) monitoring, a paradigm shift towards incorporating distributed sensing approaches using low-cost sensors has begun [1]. In past research, early generations of low-cost particle sensors based on IR light scattering have been compared with official measurement stations, showing that these sensors can in principle capture th...

Air quality and the associated subjective and health-related quality of life are among the important topics of urban life in our time. In the past years, a paradigm shift towards integrating mobile PM monitors to form distributed sensing networks has begun in air quality sensing [1]. In addition to new and promising measurement approaches, large-sc...

Die räumliche und zeitliche Verteilung von Luftschadstoffen in Städten ist sehr variabel, da sie von unterschiedlichen Einflüssen abhängt, die von den Emittenten (räumliche Anordnung, zeitliche Aktivität) als auch den meteorologischen Bedingungen, der Bebauung und den chemischen Prozessen kommen. Zurzeit werden Verunreinigung der Luft mit relativ w...

The ubiquity of ever-connected smartphones has lead to new sensing paradigms that promise environmentalmonitoring in unprecedented temporal and spatial resolution. Everyday people may use low-cost sensors to collect environmental data. However, measurement errors increase over time, especially with low-cost airquality sensors. Therefore, regular ca...

Wearables like smartwatches or fitness trackers are increasingly entering everyday life. This offers new and unexplored opportunities to use their unique features - like the ability to act as vibrotactile actuators - as interfaces in computer games to increase game immersion. Current tactile cues in games are mostly restricted to event based-feedba...

In this paper, we present the VibrationCap system and its evaluation. Two main contributions are made. First, we provide recommendations for wearable- and technology-design of head-worn vibration displays. Second, we study how accurately individual vibrations can be localized on the head, depending on their position. The VibrationCap is an unobtrus...

Embedded hardware platforms that carry sensors and actuators play a major role in many Ubicomp applications. With the advent of DIY platforms as Arduino, hardware development for embedded systems is in the reach of everybody today. These projects often build on low-fidelity systems or even prototypes and are often carried out by engineers with no s...

User studies are an important part in the design of socio-technical systems. However, Computer Science students and practitioners in Ubicomp often have not been trained in designing and conducting experimental studies. To help bridging this gap, this paper presents a (very) short tutorial on how (not) to design and conduct experimental studies and...

As ubiquitous computing solutions are becoming part of everyday life, their design has to account for the challenges of complex sociotechnical systems. Unexpected behavior and interactions between multiple systems, users and stakeholders challenge design methods and raise the risk of failure. This workshop provides an opportunity for the UbiComp co...

Citizen Science with mobile and wearable technology holds the possibility of unprecedented observation systems. Experts and policy makers are torn between enthusiasm and scepticism regarding the value of the resulting data, as their decision making traditionally relies on high-quality instrumentation and trained personnel measuring in a standardize...

Air Quality and with this, subjective and health related life quality, is one of the biggest topics of modern cities and developing countries in our time. For many regions and cities it is difficult to take action regarding air quality in mobility, residential or working areas, because there is no fine-meshed and profound database available for mak...

Participatory Sensing, i.e. collaboratively taking sensor measurements with mobile devices in a Citizen Science fashion, has become increasingly popular. Because such scenarios often require a critical mass of users, applying gamification to different areas in order to increase user engagement has been proposed. However, existing attempts often def...

Engine-less flight like Paragliding or Hang Gliding heavily relies on leveraging thermals to prolong the experience. At the same time, descending air currents or abnormal weather conditions potentially lead to extreme sink or lift, endangering the pilots. So-called variometers measure the vertical velocity and use auditory and visual encoding to in...

Fueled by the increasing proliferation of citizen generated spatio-temporal data -- especially in participatory urban infrastructure monitoring -- municipal authorities are in need for ways to process and understand increasingly overwhelming amounts of data. However, duplicate issue reporting by citizens such as broken traffic lights, potholes or g...

Ever-connected smart phones and advanced sensors have lead to new sensing paradigms that promise environmental monitoring in unprecedented spatio-temporal resolution. Especially in air quality sensing with low-cost sensors, regular in-situ device calibration is a helpful approach to ensure data quality. In participatory sensing scenarios, privacy i...

Air quality is an aspect that gains more and more attention in the general public, as knowledge on the harmful effects on human health and the environment increase. Along with this, interest in low-cost instrumentation that enables end-users to measure particulate matter has grown, both for individuals, as well as for the use in distributed sensing...

Personal and participatory environmental sensing, especially of air quality, is a topic of increasing importance. However, as the employed sensors are often cheap, they are prone to erroneous readings, e.g. due to sensor aging or low selectivity. Additionally, non-expert users make mistakes when handling equipment. We present an elegant approach th...

We present MoA², a context-aware smartphone app for the ambulatory assessment of mood, tiredness and stress level. In principle, it has two features: (1) mood assessment and (2) mood recognition. The mood assessment system combines benefits of state of the art approaches. The mood recognition is concluded by smartphone-based wearable sensing. In a...

An increasing corpus of research focuses on inferring contexts solely through analysis of changes in surrounding wireless signals without the subject carrying a device (device-free). This paper takes device-free recognition a step further: We present WiDisc, a novel device-free RF system for distinguishing three subject classes (e.g. tall, medium,...

This work presents the bPart, a highly integrated autonomous sensor platform for use with mobile phones and devices. It consists of a Bluetooth Low Energy (BLE) radio and several MEMS sensors, all integrated in a volume of less than 1cm³, including the battery. Aside from the wireless transceiver, the bPart features sensors for ambient illumination...

This paper presents a comparative study of six different tag and context based authentication schemes for open Wi-Fi access. All of the implemented methods require only a smartphone and an HTML5 capable webbrowser, making them interchangeable and easy to incorporate into existing infrastructure. We recruited 22 participants for the study and used t...

Human Activity Recognition (HAR) using accelerometers has been studied intensively in the past decade. Recent HTML5 methods allow sampling a mobile phone's sensors from within web pages. Our objective is to leverage this for the creation of individual activity recognition modules that can be included into web applications to allow them to gain cont...

This paper presents a mobile, low-cost particulate matter sensing approach for the use in Participatory Sensing scenarios. It shows that cheap commercial off-the-shelf (COTS) dust sensors can be used in distributed or mobile personal measurement devices at a cost one to two orders of magnitude lower than that of current hand-held solutions, while r...

This paper presents an energy saving concept for home and office environments, which proposes to design a multi-layered architecture for an automatic monitoring and control. Based on heterogeneous wireless sensor networks and a context awareness system, the acquired data will be interpreted into different energyrelated contextual information. A cor...

We are facing a restructuring of the power industry towards a smart grid. The vision of the smart grid represents not only the creation of intelligent power supply networks to allow efficient and reliable use of energy resources, but also the redesign of the market structure coupled with it. In order to develop a smart grid-ready power market, the...

This paper proposes using a 2D waveguide for a novel means of authentication in public Wi-Fi infrastructures. The design of the system is presented, and its practicability and usability is comparatively discussed with that of five other tag and context based authentication schemes, two of which have not been previously realized. In accordance with...

This work discusses ways of measuring particulate matter with mobile devices. Solutions using a dedicated sensor device are presented along with a novel method of retrofitting a sensor to a camera phone without need for electrical modifications. Instead, the flash and camera of the phone are used as light source and receptor of an optical dust sens...

This work presents a system that makes use of the Microsoft Kinect to enable Point&Click interaction for the control of appliances in smart environments. A backend server determines through collision detection which device the user is pointing at and sends the respective control interface to the user's smartphone. Any commands the user issues are t...

A variety of studies in the past decades have shown that fine particulate matter can be a serious health hazard, contributing to respiratory and cardiovascular disease. Due to this, more and more regulations defining certain permissible concentration limits have been set by governments around the world. However, current standard measurement equipme...

Participatory Urban Sensing scenarios have increasingly been studied in the past years. At the same time, society's concern about the effects of pollutants on people's personal health as well as on the environment grew. This, in conjunction with studies that helped to give a better understanding of those effects, lead to new and stricter regulation...

Context-based authentication methods enable the unobtrusive establishment of authentication or even secure keys. While several context-based authentication methods have been proposed recently, often the entropy of the seed for the cryptographic keys is not exploited. We study the entropy of audio fingerprints which can be utilized to pair devices i...

This paper presents an energy-saving concept for home/office environments, which proposes to design a multi-layered architecture for an automatic monitoring and control. Based on wireless sensor networks and a context awareness system, the acquired data will be interpreted into different energy-related contextual information. A correlation module u...

Smart phones have become a powerful platform for wearable context recognition. We present a service-based recognition architecture which creates an evolving classification system using feedback from the user community. The approach utilizes classifiers based on fuzzy inference systems which use live annotation to personalize the classifier instance...

In mobile and ubiquitous computing, there is a strong need for supporting different users with different interests, needs, and demands. Activity recognition systems for context aware computing applications usually employ highly optimized off-line learning methods. In such systems, a new classifier can only be added if the whole recognition system i...

During the last years, mobile phones more and more have come into the focus of interest of activity recognition research. The research community is faced with two system problems: First, how to separate and schedule activity recognition functionality, and second, how to minimize power consumption. In this paper we (a) propose the use of a modular c...