Utility-driven Data Acquisition in Participatory Sensing

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Despite the increasing number of climate and sustainability pledges, knowledge of how to reach those targets within a given system – systems and transformation knowledge – is often lacking. Backcasting can be highly relevant for tackling this transformatio ...

Rapid urbanization, alongside escalating resource depletion and ecological degradation, underscores the urgent need for innovative paradigms in urban development. In response, sustainable smart cities are increasingly leveraging advanced technological fram ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

Multi-Scale computing systems aim at bringing the computing as close as possible to the data sources, to optimize both computation and networking. These systems are composed of at least three computing layers: the terminal layer, the edge layer, and the cl ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Despite the wealth of research on smart cities, there is a lack of studies examining interlinkages between smart cities and Sustainable Development Goals (SDGs). In other words, there is limited research on how implementing smart city solutions can lead to ...

Vehicle sharing systems (VSSs) allow users to rent vehicles for a short period of time, in a more flexible and convenient manner compared to the traditional vehicle rental services. The long-term VSS subscription replaces the need for contract signing for ...

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the cost of over-appropriating a common-pool resource (which diminishes future stock, and thus harvest, for everyone) ...

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

The social discourse surrounding the climate emergency progressively infuses the society, transforming into both micro- and macro-social injunctions to change. Yet, society - grounded in a territorial, social, and cultural contingency - appears to resist t ...

To ensure the long-term sustainable use of African Great Lakes (AGL), and to better understand the func-tioning of these ecosystems, authorities, managers and scientists need regularly collected scientific data and information of key environmental indicato ...

While technology is often claimed to be “democratizing”, the technologizing of society has more often yielded undemocratic or even anti-democratic outcomes. Is technology fundamentally at odds with democracy, or is it merely a rich and infinitely-adaptable ...

We consider the problem of enhancing user privacy in common data analysis and machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples from a generative adversarial network. We propose employing ...

In this thesis, we present a theory of value for the design and analysis of service ecosystems. The theory is based on general systems thinking. The concept of a system is used for relating knowledge from different disciplines (such as software engineering ...

Problem statement. Cities hold a central role in global efforts towards sustainability, and integrating sustainability concerns into the governance of cities constitutes an increasingly urgent challenge. One avenue holding promise in this respect concerns ...

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters als ...

Utility-driven Data Acquisition in Participatory Sensing

Chattez avec Graph Search

Carving the transformation pathways to sustainable futures: A novel analytical framework for backcasting in sustainability transitions

Artificial intelligence of things for sustainable smart city brain and digital twin systems: Pioneering Environmental synergies between real-time management and predictive planning

Reliable data-driven decision-making through optimal transport

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Special Session: Challenges and Opportunities for Sustainable Multi-Scale Computing Systems

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Smart cities and sustainable development goals (SDGs): A systematic literature review of co-benefits and trade-offs

Demand-based operations of vehicle sharing systems

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

AI-driven Prices for Externalities and Sustainability in Production Markets

E-Scan: Consuming Contextual Data with Model Plugins

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

Resistances to change in urban travel behaviors

Need for harmonized long-term multi-lake monitoring of African Great Lakes

Technologizing Democracy or Democratizing Technology? A Layered-Architecture Perspective on Potentials and Challenges

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

A Theory of Value for Service Ecosystems

From metrics towards meaningful assessments of urban sustainability - exploring visions, frameworks and indicators

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge