2023 Proceeding
With the rapid revolution and increasing availability of geospatial data, not only academia but also industry aspire for solutions to further leverage the big data and AI technologies to create new products, improve efficiencies and provide novel solutions to existing problems. However, despite the widespread interest, there is a lack of communication between the researchers in academia and industry, limiting advancements at the intersection. Academia often has limited access to the rich and potentially useful big geospatial datasets and related real problems. In addition, the solutions proposed by the academic researchers alone are usually developed for small scale with many assumptions, leaving a less-attended gap between methods and their applicability at scale for industrial applications. On the other hand, industry has the data and problems at scale. However, since existing research is often not on par, industry researchers may lean towards using the traditional approaches that are developed without spatial consideration (e.g., ignoring spatial and temporal dependencies), and project teams have limited time and efforts to dive deep on the development of novel techniques that can be high-risk but high-potential. This opens up opportunities for synergistic collaboration between industrial practitioners and academic researchers. The 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications (GeoIndustry 2023) is to offer a forum to exchange thoughts and ideas between industry and academia and reduce the siloed efforts. At the same time, the collaborations, via invited and regular talks, can not only accelerate the research-to-impact cycle, but also foster workforce development for future geospatial researchers.
Proceeding Downloads
Spatial experiment identification (SPEX-ID): a method to identify experimental conditions from spatial information in digital agricultural data and beyond
On-farm experiments (OFE) are the cornerstone of evaluating interventions on important outcomes like crop yield, disease resistance, soil fertility, and more. However, prospectively planning and implementing all OFE of interest is challenging in ...
Floorplan Generation from Noisy Point Cloud
Floorplans are useful for navigating indoor spaces, for resource allocation and for indoor space management among many others. But in the absence of readily available digital floorplans, these are hard to generate. In this work, we enhance the ...
A New Approach to Assessing Perceived Walkability: Combining Street View Imagery with Multimodal Contrastive Learning Model
Walkability is becoming increasingly important in urban planning, public health, and environmental protection. Traditional assessment tools like streetscape images and semantic segmentation focus on objective factors, while questionnaires as the main ...
Exploring The Use of OpenStreetMap Data (OSM) and GPS Traces for Validating Driving Routes and Identifying Prohibited Maneuvers in Direction Services
- Antonios Karatzoglou,
- Tijana Bekic,
- Vashutosh Agrawal,
- Mohit Khanna,
- Aleksandar Matejevic,
- Varun Kakkar,
- Michael R. Evans,
- Aleksandar Samardzija,
- Jacob Whitbeck,
- Dragomir Yankov,
- Nikola Perin,
- Nikola Todic,
- Goran Predovic
As people increasingly adopt a more flexible and mobile way of living, map applications and navigation services have gained increasingly in importance. In order for these services to be useful to their users, their providers need to ensure and maintain ...
LocFree: WiFi RTT-based Device-Free Indoor Localization System
Gaining knowledge of a person's location in the environment without needing a specialized device raises the need for device-free indoor localization systems that could be leveraged in many applications including IoT, security, etc. Wi-Fi is one of the ...
Cellular Network Optimization by Deep Reinforcement Learning and AI-Enhanced Ray Tracing
In this paper we study the use of deep reinforcement learning that is supported by a ray tracer, on top of a detailed 3D model of the geospatial environment, for optimization of antenna tilts in cellular networks. We propose two novel mechanisms---...
Optimization of shared bicycle location in Wuhan city based on multi-source geospatial big data
With urban development and a growing focus on sustainability, shared bicycles have become a popular mode of eco-friendly transportation. However, issues like chaotic parking, excessive deployment, and suboptimal distribution need solutions. This study ...
Index Terms
- Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications
Recommendations
IWGS 2016 workshop report: The 7th ACM SIGSPATIAL International Workshop on GeoStreaming: San Francisco, CA, USA - October 31, 2016
The ACM SIGSPATIAL International Workshop on Geostreaming (IWGS) was held for the seventh time in conjunction with the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACMGIS 2016). The workshop has been a ...