arXiv:2603. 21639v2 Announce Type: replace-cross Abstract: Accurately estimating human mobility in peripheral regional economies presents a fundamental measurement challenge: physical ground-truth sensors are sparse, behavioral intent signals are heterogeneous, and environmental friction introduces systematic bias into demand inference.
arXiv:2608. 09255v1 Announce Type: new Abstract: Residential energy estimates are often needed before detailed envelope characteristics, equipment efficiencies, infiltration, sensor, or billing data are available.
arXiv:2606. 15890v1 Announce Type: new Abstract: Understanding urban wellbeing from multimodal data requires integrating heterogeneous spatial and temporal signals, posing significant challenges for current multimodal large language models (MLLMs).
arXiv:2606. 16580v1 Announce Type: new Abstract: Top-soil organic carbon (SOC) prediction is fundamental to agricultural sustainability, land use policy and fertilization planning.
arXiv:2507. 00945v2 Announce Type: replace Abstract: Short-term forecasting of aggregated human mobility flows supports urban planning, intelligent transportation systems, and emergency response, yet existing models often require substantial mobility history and learn spatial structure implicitly through grids or graphs.
arXiv:2606. 24781v1 Announce Type: new Abstract: While the field of Human Activity Recognition (HAR) continues to draw interest from researchers and advance in important ways, some key challenges remain.
arXiv:2606. 03358v1 Announce Type: new Abstract: Smart meter data can reveal sensitive socio-demographic characteristics of households, raising privacy concerns.
arXiv:2603. 13343v3 Announce Type: replace-cross Abstract: Predictive maintenance for connected vehicles offers the potential to reduce unexpected breakdowns and improve fleet reliability, but most existing systems rely exclusively on internal diagnostic signals and are validated on simulated or industrial benchmark data.
arXiv:2411. 10959v5 Announce Type: replace-cross Abstract: We study causal inference in experiments and quasi-experiments, where the economic outcome is imperfectly measured by a remotely sensed variable.
arXiv:2608. 00012v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly used to interpret Earth observation data, yet their capability to support real-world disaster emergency response remains insufficiently evaluated.
arXiv:2606. 10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Category 1 under the Corporate Sustainability Reporting Directive (CSRD), which requires disclosure for fiscal years starting January 2024.
arXiv:2606. 11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify because multi-sensor observations are rarely available in consistent, analysis-ready form at the necessary spatiotemporal scales.
arXiv:2607. 13558v1 Announce Type: new Abstract: Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and environmental monitoring.