Ella Peltonen

University of Oulu · Center for Ubiquitous Computing

Not all research leads to fruitful results; trying new ways or methods may surpass state of the art, but sometimes the hypothesis is not proven, the improvement is insignificant, or the system fails because of a design error done years ago in previous works. In a systems discipline like pervasive computing, there are many sources of errors, from ha...

The International Conference on Pervasive Computing and Communications (IEEE PerCom) is a CORE 2021 A* conference (top 7% of ranked venues) that aims to present scientific advances in a broad spectrum of technologies and topics in ubiquitous/pervasive computing, including wireless networking, mobile and distributed computing, sensor systems, ambien...

Not all research leads to fruitful results; trying new ways or methods may surpass the state of the art, but sometimes the hypothesis is not proven or the improvement is insignificant. In a systems discipline like pervasive computing, there are many sources of errors, from hardware issues over communication channels to heterogeneous software enviro...

Efficient resource usage in edge computing requires clever allocation of the workload of application components. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks—a phenomenon we present as a reallocation st...

Over the past years, cars' computing, sensing, and networking capabilities have rapidly increased, and the automotive development aims for autonomous driving. However, the driver is still the focal point for decision making. It has to be alert at all times to avoid traffic accidents due to human factors like tiredness, inattentiveness, and intoxica...

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization,...

Smartphones are an integral part of our daily life, bringing both positive and negative impacts with them. Recent studies suggest that extensive and untimely smartphone usage directly affects circadian rhythm, i.e. alertness-sleepiness cycle. In this paper, we analyse sleep quality data collected through a wearable ring together with the smartphone...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Edge Intelligence (EI) is an emerging computing and communication paradigm that enables Artificial Intelligence (AI) functionality at the network edge. In this article, we highlight EI as an emerging and important field of research, discuss the state o...

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization,...

While the use of smartphones in extreme temperatures does not necessarily occur every day nor in all parts of the world, numerous use cases can be highlighted where the use of smartphones in cold temperatures is mandatory. Modern smartphones are designed to function in a wide range of temperatures, but when exposed to extreme cold temperatures the...

Smartphones can be considered the cheapest and well-penetrated devices for collecting everyday human behaviour data. However, smartphones, as any battery-dependant electronic devices, face a number of problems when exposed to below-freezing conditions, from sudden crashes and decreased battery life to challenging usage experiences such as freezing...

Background Depression is a prevalent mental health challenge. Current depression assessment methods using self-reported and clinician-administered questionnaires have limitations. Instrumenting smartphones to passively and continuously collect moment-by-moment data sets to quantify human behaviors has the potential to augment current depression ass...

Mobile applications and online service providers track our virtual and physical behaviour more actively and with a broader scope than ever before. This has given rise to growing concerns about ethical personal data management. Even though regulation and awareness around data ethics are increasing, end-users are seldom engaged when defining and desi...

Sensor-driven IoT systems are well-known for their capacity to accelerate massive amounts of data in a comparatively short period of time. To have any use, the information delivery and decision making based on the data require efficient learning models together with dynamically deployed computing and network resources. The current cloud and high-pe...

Efficient service placement and workload allocation methods are necessary enablers for the actively studied topic of edge computing. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks – a phenomenon we presen...

Spatiotemporal interpolation provides estimates of observations in unobserved locations and time slots. In smart cities, interpolation helps to provide a fine-grained contextual and situational understanding of the urban environment, in terms of both short-term (e.g., weather, air quality, traffic) or long term (e.g., crime, demographics) spatio-te...

BACKGROUND Depression is a prevalent mental health challenge. Current depression assessment methods using self-reported and clinician-administered questionnaires have limitations. Instrumenting smartphones to passively and continuously collect moment by moment datasets to quantify human behaviours that have the potential to augment current depressi...

As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for...

Smartphone usage and sleep quality have established connections in psychological research, but in the HCI context, the topic is still understudied. In this paper, we present preliminary insights into behavioral patterns between smartphone usage and sleep quality by using crowdsensed data. We utilize a large-scale mobile usage dataset and a PHQ-8 de...

Smartwatch battery limitations are one of the biggest hurdles to their acceptability in the consumer market. To our knowledge, despite promising studies analyzing smartwatch battery data, there has been little research that has analyzed the battery usage of a diverse set of smartwatches in a real-world setting. To address this challenge, this paper...

Advances in technology and data analysis provide rich opportunities for developing intelligent environments assisting their inhabitants, so-called smart environments or smart spaces. Enhanced with technology, sensors, user interfaces, and various applications, such smart spaces are capable of recognizing users and situations they are in, react acco...

Internet of Things technologies and platforms can provide both novel applications and business strategies for the companies of different technological application areas. However, risks for intensive participation in utilizing novel and expensive technologies into their business and products, might be considered risky by small and medium-sized enter...

In this white paper we provide a vision for 6G Edge Intelligence. Moving towards 5G and beyond the future 6G networks, intelligent solutions utilizing data-driven machine learning and artificial intelligence become crucial for several real-world applications including but not limited to, more efficient manufacturing, novel personal smart device env...

The commercial launch of 6G communications systems and United Nations Sustainable Development Goals, UN SDGs, are both targeted for 2030. 6G communications is expected to boost global growth and productivity, create new business models and transform many aspects of society. The UN SDGs are a way of framing opportunities and challenges of a desirabl...

In this article, we study the scaling up of edge computing deployments. In edge computing, deployments are scaled up by adding more computational capacity atop the initial deployment, as deployment budgets allow. However, without careful consideration, adding new servers may not improve proximity to the mobile users, crucial for the Quality of Expe...

In the context of evolving communication technologies like 5G and the inevitable 6G, edge computing has a significant role to play. Cloud computing is inadequate at handling the real-time data processing and analysis requirements the above advancements will entail. However, edge computing has its own set of challenges, intensified further upon empl...

In this paper, we describe how the microservices paradigm can be used to design and implement distributed edge services for Internet of Things applications. As a case study, traditionally monolithic user mobility analysis service is developed, with distributed and extendable microservices, for the standardized ETSI MEC system reference architecture...

As fifth generation (5G) research is maturing towards a global standard, the research community must focus on the development of beyond-5G solutions and the 2030 era, i.e. 6G. It is not clear yet what 6G will entail. It will include relevant technologies considered too immature for 5G or which are outside the defined scope of 5G. This white pape...

As fifth generation (5G) research is maturing towards a global standard, the research community has started to focus on the development of beyond-5G solutions and the 2030 era, i.e. 6G. In the future, our society will be increasingly digitised, hyper-connected and globally data driven. Many widely anticipated future services will be critically depe...

Prevalent weather prediction methods are based on sensor data, collected by satellites and a sparse grid of stationary weather stations. Various initiatives improve the prediction models by including additional data sources such as mobile weather sensors, mobile phones, and micro weather stations of, for example, smart homes. The underlying computi...

Wearable sensors have become more commonly used in everyday basis and powerful in terms of computational capacity and sensing resources, including capability to collect data from different bio-signals. The data collected from everyday wearables offers huge opportunities to monitor people's everyday life without expensive laboratory measurements, in...

Popularity of mobile apps is traditionally measured by metrics such as the number of downloads, installations, or user ratings. A problem with these measures is that they reflect usage only indirectly. Indeed, retention rates, i.e., the number of days users continue to interact with an installed app, have been suggested to predict successful app li...

Edge and fog computing, prominent parts of the up-coming 5G mobile networks and future 6G technologies, promise to reduce applications' latencies, improve controls on privacy, and reduce network bandwidth usage. The promises are delivered by pulling computations from the remote cloud to close to the devices, where data is generated and applications...

Edge and Fog Computing platforms, together with soon-to-come 5G technologies and future 6G visions, enable local, low-latency computational resources. At the same time, rising awareness of novel artificial intelligence and other data-driven applications sets a demand of trustworthy computational power close to the client. Our research aims to bring...

Rising utilization of novel artificial intelligence and other data-driven applications sets a demand for privacy-preserving large-scale data management. In the current, cloud-centric model, trust is placed on third parties that collect, aggregate, link and analyse personally identifiable information (PII) with artificial intelligence (AI) and machi...

Edge computing, together with soon-to-come 5G technologies and future 6G vision, enable distributed computing platforms with computational and data resources in the close proximity to the users/clients with low-latency connections. Traditional data flow in the Internet of Things is vertical , spanning between the cloud, the network infrastructure c...

Edge computing, a key part of the upcoming 5G mobile networks and future 6G technologies, promises to distribute cloud applications while providing more bandwidth and reducing latencies [1]. The promises are delivered by moving application-specific computations between the cloud, the data producing devices, and the network infrastructure components...

Mobile, vehicle-installed road weather sensors are becoming ubiquitous. While mobile sensors are often capable of making observations on a high frequency, their reliability and accuracy may vary. Large-scale road weather observation and forecasting are still mostly based on stationary road weather stations (RWS). Though expensive, sparsely located...

Residual plot of the inference model. (TIF)

Q-Q plot of the mobile sensor calibration level random effect. (TIF)

Q-Q plot of a sample of 100 residuals. (TIF)

Q-Q plot of the RWS sensor calibration level random effect. (TIF)

While mobile apps have become an integral part of everyday life, little is known about the factors that govern their usage. Particularly the role of geographic and cultural factors has been understudied. This article contributes by carrying out a large-scale analysis of geographic, cultural, and demographic factors in mobile usage. We consider app...

The Carat project started in 2012 has collected over 1.5 TB of data from over 850,000 mobile users all over the world. The project uses Apache Thrift to transmit data, and Apache Spark to run data analysis tasks, and the gist of the Carat analysis method has been published. While the Carat application code is open source, the data is much harder to...

The value of mobile apps is traditionally measured by metrics such as the number of downloads, installations, or user ratings. A problem with these measures is that they reflect actual usage at most indirectly. Indeed, analytic companies have suggested that retention rates, i.e., the number of days users continue to interact with an installed app a...

The increased complexity of smartphone applications, and the increasing number of system settings affecting these applications, has made it difficult to understand and optimize battery use. This article summarizes the authors' recent work on developing a novel crowdsourced solution for characterizing energy consumption of system settings, subsystem...

The question "Where has my battery gone?" remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for cons...

The question 'Where has my battery life gone?' remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for...