Sasu Tarkoma

University of Helsinki | HY · Department of Computer Science

p>We develop a portable and affordable solution for estimating personal exposure to black carbon (BC) using low- cost sensors and machine learning. Our approach uses other pollutants and environmental variables as proxies for estimating the concentrations of BC and combines this with machine learning based sensor calibration to improve the quality...

p>We develop a portable and affordable solution for estimating personal exposure to black carbon (BC) using low- cost sensors and machine learning. Our approach uses other pollutants and environmental variables as proxies for estimating the concentrations of BC and combines this with machine learning based sensor calibration to improve the quality...

This paper proposes the neural publish/subscribe paradigm, a novel approach to orchestrating AI workflows in large-scale distributed AI systems in the computing continuum. Traditional centralized broker methodologies are increasingly struggling with managing the data surge resulting from the proliferation of 5G systems, connected devices, and ultra...

Cities play an important role in achieving sustainable development goals (SDGs) to promote economic growth and meet social needs. Especially satellite imagery is a potential data source for studying sustainable urban development. However, a comprehensive dataset in the United States (U.S.) covering multiple cities, multiple years, multiple scales,...

Carbon monoxide (CO) and Nitrogen dioxide (NO2) are major air pollutants that have the potential to affect human health adversely. There is a lack of useful information regarding the spatial distribution and temporal variability of CO and NO2 emissions in major metropolitan areas. The primary goal of this research is to provide a geospatial data me...

Unmanned Aerial Vehicles (UAVs) equipped with air quality sensors offer a powerful solution for increasing the spatial and temporal resolution of air quality data, searching and detecting emission sources, and monitoring emissions from fixed and mobile sources. Despite the numerous advantages of using UAVs, their use, however, presents several chal...

Spark is one of the most popular big data analytical platforms. To save time, achieve high resource utilization, and remain cost-effective for Spark jobs, it is challenging but imperative for data scientists to configure suitable resource portions.In this paper, we investigate the proper parameter values that meet workloads’ performance requirement...

The rapid growth of megacities has led to higher levels of air pollution in cities. To supplement fixed air quality monitoring sites, the megacities offer an unprecedented opportunity to deploy air quality sensors on public transportation systems, and thus enable air quality monitoring at different locations in the city within the routes of the tra...

Mobile apps have become an indispensable part of people’s daily lives. Users determine what apps to use and when and where to use them based on their tastes, interests, and personal demands, depending on their personality traits. This paper aims to infer user profiles from their spatiotemporal mobile app usage behavior. Specifically, we first trans...

Satellite imagery depicts the earth’s surface remotely and provides comprehensive information for many applications, such as land use monitoring and urban planning. Existing studies on unsupervised representation learning for satellite images only take into account the images’ geographic information, ignoring human activity factors. To bridge this...

The present article contributes a research vision for virtual sensing that combines Artificial Intelligence (AI) and Internet of Things (IoT) to increase the coverage of air quality information. Virtual sensors take advantage of correlations between different pollutants to estimate the concentrations of pollutants for which no affordable sensors ar...

The COVID-19 pandemic highlighted the need to prioritise mature digital health and data governance at both national and supranational levels to guarantee future health security. The Riyadh Declaration on Digital Health was a call to action to create the infrastructure needed to share effective digital health evidence-based practices and high-qualit...

Air quality low-cost sensors are affordable and can be deployed in massive scale in order to enable high-resolution spatio-temporal air pollution information. However, they often suffer from sensing accuracy, in particular when they are used for capturing extreme events. We propose an intelligent sensors calibration method that facilitates correcti...

Dangers associated with poor air quality are driving deployments of air quality monitoring technology worldwide. Having a comprehensive understanding of the health effects of pollutants requires understanding both the distribution and dispersion of pollutants in the environments, but currently this information is highly difficult to capture. This a...

In a post-pandemic world, remaining vigilant and maintaining social distancing are still crucial so societies can contain the virus and the public can avoid disproportionate health impacts. Augmented Reality (AR) can visually assist users in understanding the distances in social distancing. However, integrating external sensing and analysis is requ...

Smart spaces, physical spaces that are integrated with sensor-enabled IoT devices, are a powerful paradigm for optimizing the operations of the space and improving its quality for the occupants. Managing the applications and services running in the space is a complex task as the operations of the devices and services are dependent on the physical c...

Underwater environments are emerging as a new frontier for data science thanks to an increase in deployments of underwater sensor technology. Challenges in operating computing underwater combined with a lack of high-speed communication technology covering most aquatic areas means that there is a significant delay between the collection and analysis...

The architectures of mobile networks have seen an unprecedented techno-economic transformation, fusing the telcommunications world within the cloud world, adding the spices of Software Engineering to the overall system design, and ultimately yielding the concept of Telco Cloud. This has brought significant benefits in terms of reducing expenditure...

Air pollution is known to be harmful for human health and environments. The official air quality monitoring stations have been established across many smart cities around the world. Unfortunately, these monitoring stations are sparsely located and consequently do not provide high resolution spatio-temporal air quality information. This paper demons...

The Internet has been experiencing immense growth in multimedia traffic from mobile devices. The increase in traffic presents many challenges to user-centric networks, network operators, and service providers. Foremost among these challenges is the inability of networks to determine the types of encrypted traffic and thus the level of network servi...

This article contributes a research vision for using edge computing to deliver the computing infrastructure for emerging smart megacities, with use cases, key requirements, and reflections on the state of the art. We also address edge server placements, a key challenge for edge computing adoption.

p>Autonomous drones are reaching a level of maturity when they can be deployed in cities to support tasks ranging from medicine or food delivery to environmental monitoring. These operations rely on powerful AI models integrated into the drones. Ensuring these models are robust is essential for operating in cities as any errors in the decisions of...

p>Autonomous drones are reaching a level of maturity when they can be deployed in cities to support tasks ranging from medicine or food delivery to environmental monitoring. These operations rely on powerful AI models integrated into the drones. Ensuring these models are robust is essential for operating in cities as any errors in the decisions of...

Context-based authentication has been proposed as a way to enable secure authentication with minimal or even no user interaction requirements by using sensor data to ensure the device being authenticated is in possession of the person initiating the authentication request. A key limitation of practically all context-based authentication systems is...

Covert surveillance devices ranging from miniature cameras to voice recorders are increasingly affordable and accessible on the market, raising concerns about surreptitious and unauthorized observation of people. This article contributes an innovative method for discovering covert surveillance devices using thermal imaging integrated with off-the-s...

Understanding economic development and designing government policies requires accurate and timely measurements of socioeconomic activities. In this paper, we show how to leverage city structural information and urban imagery like satellite images and street view images to accurately predict multi-level socioeconomic indicators. Our framework consis...

Applications based on machine learning (ML) are greatly facilitated by mobile devices and their enormous volume and variety of data. To better safeguard the privacy of user data, traditional ML techniques have transitioned toward new paradigms like federated learning (FL) and split learning (SL). However, existing frameworks have overlooked device...

We quantify and derive a general model for the collaboration stability of human mobility and demonstrate its importance for networking applications. Our results demonstrate that collaboration opportunities are highly dependent on the context where they take place, with diurnal patterns and spatial characteristics being particularly important.

Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications. Traditional ML techniques have shifted toward new paradigms such as federated (FL) and split learning (SL) to improve the protection of user's data privacy. However, these paradigms often rely on server(s) located in...

Formaldehyde is a carcinogenic indoor air pollutant emitted from common wood-based materials. Low-cost sensing of formaldehyde is difficult due to inaccuracies in measuring low concentrations and susceptibility of sensors to changing indoor environmental conditions. Currently gas sensors are calibrated by manufacturers using simplistic models which...

The COVID-19 pandemic is posing significant challenges to public transport operators by drastically reducing demand while also requiring them to implement measures that minimize risks to the health of the passengers. While the collective scientific understanding of the SARS-CoV-2 virus and COVID-19 pandemic are rapidly increasing, currently there i...

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requ...

We present a research vision for deep learning (DL) in the oceans, collating applications and use cases as well as identifying opportunities, constraints, and open research challenges. Integrating DL in underwater explorations can automate and scale up monitoring as well as highlight practical challenges in enabling underwater operations.

We contribute a novel model evaluation technique that divides available measurements into training and testing sets in a way that adheres to the requirements imposed on professional monitoring stations. We perform extensive and systematic experiments with a wide range of state-of-the-art calibration models to demonstrate that our approach provides...

As evidence of adverse health effects due to air pollution continues to increase, the World Health Organization (WHO) recently published its latest edition of the global air quality guidelines (World Health Organization, 2021). Although not legally binding, the guidelines aim to provide a framework in which policymakers can combat air pollution by...

Littering is a significant challenge for environmental sustainability and a major burden for cities and densely populated areas. Current solutions for litter monitoring, such as litter watch campaigns and city-operated litter collection, are costly and challenging to conduct at a large scale. This article presents a vision for using autonomous grou...

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,...

As smartphones have become indispensable personal devices, the number of smartphone users has increased dramatically over the last decade. These personal devices, which are supported by a variety of smartphone apps, allow people to access Internet services in a convenient and ubiquitous manner. App developers and service providers can collect fine-...

Connected vehicles, whether equipped with advanced driver-assistance systems or fully autonomous, require human driver supervision and are currently constrained to visual information in their line-of-sight. A cooperative perception system among vehicles increases their situational awareness by extending their perception range. Existing solutions fo...

Importance: COVID-19 has highlighted widespread chronic underinvestment in digital health that hampered public health responses to the pandemic. Recognizing this, the Riyadh Declaration on Digital Health, formulated by an international interdisciplinary team of medical, academic, and industry experts at the Riyadh Global Digital Health Summit in A...

Lung-deposited surface area (LDSA) has been considered to be a better metric to explain nanoparticle toxicity instead of the commonly used particulate mass concentration. LDSA concentrations can be obtained either by direct measurements or by calculation based on the empirical lung deposition model and measurements of particle size distribution. Ho...

Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given day. In practice, NPF event identification is performed visually by classifying the NPF event...

Retrieving atmospheric environmental parameters such as atmospheric horizontal visibility and mass concentration of aerosol particles with a diameter of 2.5 or 10 ${\mu }\text{m}$ or less (PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> , PM <sub xmlns:mml="http://www.w3.org/1998/Math/Ma...

Forecasting electricity load has a significant role in the planning and management of sustainable power systems. In societies, the cumulative effects of social, economic, technical, environmental, and cultural factors on electricity consumption make forecasting electricity load a complex and demanding challenge. This necessitates developing robust...

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...

The Internet has been experiencing immense growth in multimedia traffic from mobile devices. The increase in traffic presents many challenges to user-centric networks, network operators, and service providers. Foremost among these challenges is the inability of networks to determine the types of encrypted traffic and thus the level of network servi...

Our devices can use a wide range of communication technologies such as multiple cellular technologies (4G/5G), WiFi, and also Ethernet. At the same time, applications have a choice of a wide range of transport protocols such as QUIC and TCP that can be fine-tuned and optimized according to their needs. However, in spite of these advances, offering...

Air pollution is a contributor to approximately one in every nine deaths annually. Air quality monitoring is being carried out extensively in urban environments. Currently, however, city air quality stations are expensive to maintain resulting in sparse coverage and data is not readily available to citizens. This can be resolved by city-wide partic...

Mobility is a fundamental characteristic of human society that shapes various aspects of our everyday interactions. This pervasiveness of mobility makes it paramount to understand factors that govern human movement and how it varies across individuals. Currently, factors governing variations in personal mobility are understudied with existing resea...

The proliferation of smartphones and mobile communication has enabled users to capture images or videos and share them immediately on social networking and messaging platforms. These platforms are also used to manipulate the masses by performing social engineering attacks by sharing fabricated images (or videos). These attacks cause public shame, e...

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,...

Energy storage systems are essential for achieving transportation electrification and, at the same time, they are advocated to be fundamental assets if properly integrated into modern power systems hosting a large amount of stochastic distributed generation. Unlocking the potential of these systems in terms of performance and cost requires new devi...

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the peri...

Urban environments with a high degree of industrialization are infested with hazardous chemicals and airborne pollutants. These pollutants can have devastating effects on human health, causing both acute and chronic diseases such as respiratory infections, lung cancer, and heart disease. Air pollution monitoring is vital not only to citizens, warni...

With the widespread application of mobile phones, it has become possible to study human mobility and travel behaviors based on cellular network data. Contrary to call detail records, the data is triggered by mobile cellular signaling and can provide fine-grained information about users' daily routines. However, it does not explicitly provide semant...

As the evidence for the adverse health effects of air pollution continues to increase, World Health Organization (WHO) recently published its latest edition of the Global Air Quality Guidelines. Although not legally binding, the guidelines aim to provide a framework in which policymakers can combat air pollution by formulating evidence-based air qu...

Massive Machine Type Communication (mMTC) has long been identified as a major vertical sector and enabler of the industry 4.0 technological evolution that will seamlessly ease the dynamics of machine-to-machine communications while leveraging 5G technology. To advance this concept, we have developed and tested an mMTC network slice called Megasense...

Internal resistance offers accurate early-stage health prediction for Li-Ion batteries. • Prediction accuracy is over 95% within the first 100 cycles at room temperature. • Demonstrated that internal resistance dynamics characterize battery homogeneity. • Homogeneous batteries can share the same early-stage prediction models. • Internal resistance...

The state of the art in designing scalable services relies on microservices with Kubernetes being the de facto platform for deploying them. While the Cloud Native Computing Foundation has standardized and improved several features in Kubernetes, one of the challenges remaining is that using multiple clouds simultaneously and dynamically, for exampl...

5G networks and beyond introduce a larger number of Network Elements (NEs) and functions than former cellular generations. The increase in NEs will, thus, result in significantly increasing the Management-Plane (M-Plane) data collected from the NEs. Therefore, the conventional centralized Network Management Systems (NMSs) will face fundamental chal...

Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given day. In practice, NPF event identification is performed visually by classifying the NPF event...

Transit activities are a significant contributor to a person’s daily exposure to pollutants. Currently obtaining accurate information about the personal exposure of a commuter is challenging as existing solutions either have a coarse monitoring resolution that omits subtle variations in pollutant concentrations or are laborious and costly to use. W...