The rapid adoption of electric vehicles (EVs) is driving increasing demand for efficient and strategically placed charging stations. While numerous studies have explored optimization methods for the placement of EV charging stations, most focus on ...

With the rapid development of electric vehicles that facilitate sustainable transportation, the need to ensure their accessibility has increased. Determining the optimal locations for extending an existing charging station network is crucial to ...

As Electric Vehicles' popularity grows, placing additional charging stations to accommodate this trend has become more critical. To optimally place them, EV charging stations should consider traffic patterns, key destinations, electric grid demand-supply ...

This study focuses on optimizing the location of electric vehicle (EV) charging stations in the state of Georgia using geospatial big data. With the growing concern about climate change and the need for a transition to sustainable energy, the adoption of ...

WiFi-based indoor localization is essential but often hampered by its dependence on specific environments and network configurations. We propose a novel solution using Language Models, like BERT, to overcome these limitations. Our approach transforms ...

The field of Geospatial Artificial Intelligence (GeoAI) has significantly impacted domain applications such as urban analytics, environmental monitoring, and disaster management. While powerful geoprocessing tools in geographic information systems (GIS) ...

The capability of constructing executable scientific workflows that integrate data, models, and domain-specific knowledge using AI tools remains quite limited. This study utilizes large language model (LLM)-powered chatbots such as ChatGPT to streamline ...

There is an urgent need for innovative technologies to detect road damage efficiently and cost-effectively. Traditional centralized deep learning models face challenges due to extensive data transfer and privacy concerns when sharing data among different ...

The rapid expansion of location-based services has generated an unprecedented volume of spatial data. Spatial grouping queries, which categorize sets of spatial objects based on their geographical properties and data characteristics, are fundamental in ...

Finding routes in road networks is a fundamental task for routing services, but most existing methods only consider the network topology and properties and cannot handle semantic queries that express user preferences or constraints. We present a novel ...

This paper focuses on GNSS trajectory aggregation, building upon the work of [4], a modular and iterative aggregation algorithm. The last allows to compute aggregated trajectories with high geometric accuracy for a set of trajectories having the same ...

Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical to healthcare, social security, and urban planning. Traditional outlier ...

Mobility patterns are inherently linked to human nature (e.g., individual variability, temporal dynamics, behavioral factors, curiosity, social interaction), making mobility prediction a multifaceted and challenging problem that requires sophisticated ...

Monitoring roundabouts and signalized intersections in a road network is important, e.g., to reduce travel time and greenhouse gas emissions. The monitoring of such junctions is a challenging problem, and current approaches mainly use high-cost solutions ...

Knowledge graphs have become a universal data representation and integration mechanism. They recently gained interest in the spatial area. Spatial-Temporal Knowledge Graphs (STKGs) in particular have been created to integrate diverse sets of spatial data ...

The idea of generalized indices is one of the success stories of database systems research. It has found its way to implementation in common database systems. GiST (Generalized Search Tree) and SP-GiST (Space-Partitioned Generalized Search Tree) are two ...

We demonstrate the Patterns of Life Simulation to create realistic simulations of human mobility in a city. This simulation has recently been used to generate massive amounts of trajectory and check-in data. Our demonstration focuses on using the ...

Urban research faces challenges in understanding and describing city regions, which are essential for urban planning and tourism management. Traditional methods rely on predefined areas and non-human-readable representations. This paper presents a new ...

This paper addresses short-term Collision-Risk-Aware ship route planning while utilizing a deep learning-based Vessel Collision Risk Assessment and Forecasting (VCRA/F) framework to quantify risks. Lacking a clear boundary between risky and viable routes,...

The fifth-generation (5G) mobile network has significantly enhanced people's lives with faster internet speed and more reliable connections. However, there is still insufficient coverage of 5G networks worldwide, requiring telecom operators to deploy ...