Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities最新文献

Detecting Street Signs in Cities Based on Object Recognition with Machine Leaning and GIS Spatial Analysis 基于机器学习和GIS空间分析的城市道路标志识别

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284571

Zihao Wu, Xiaolu Zhou

{"title":"Detecting Street Signs in Cities Based on Object Recognition with Machine Leaning and GIS Spatial Analysis","authors":"Zihao Wu, Xiaolu Zhou","doi":"10.1145/3284566.3284571","DOIUrl":"https://doi.org/10.1145/3284566.3284571","url":null,"abstract":"Road traffic signs management is a process that searches, maintains, and builds traffic signs to ensure a normal functioning of traffic systems. Automatic road traffic signs detection is an important feature in smart cities. Existing road assets management systems usually rely on labor-intensive site inventory. Some other approaches use computer vision techniques to recognize traffic signs. Recent approaches combine GPS data and vehicle-based image recognition system to detect traffic signs along with geographic information. This research provides an innovative way to detect traffic signs based on geotagged photos from Google Street View. We used the Single Shot Multi-Box Detector based on a TensorFlow framework to train the recognition model. This process is implemented on a graphic card with CUDA acceleration to speed up the training process. Results showed that stop signs at road intersections can be accurately detected over 99%. This research helps to reduce workload for traditional traffic asset inventory. Our workflow can be used to detect other traffic signs and applied to other cities.","PeriodicalId":280468,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities","volume":"459 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113994009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

D-record: Disaster Response and Relief Coordination Pipeline D-record:灾难响应和救济协调管道

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284572

Shruti Kar, Hussein S. Al-Olimat, K. Thirunarayan, V. Shalin, A. Sheth, S. Parthasarathy

引用次数: 6

An Integrated Visual Analytics Framework for Spatiotemporal Data 一个集成的时空数据可视化分析框架

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284574

Shaohua Wang, E. Zhong, Qiang Zhou, Xue Cui, Hao Lu, W. Yun, Zhongnan Hu, W. Cai, Liang Long

引用次数: 0

Real-time traffic light detection from videos with inertial sensor fusion 实时红绿灯检测视频与惯性传感器融合

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284573

Nishat Anjum Khan, R. Ansari

{"title":"Real-time traffic light detection from videos with inertial sensor fusion","authors":"Nishat Anjum Khan, R. Ansari","doi":"10.1145/3284566.3284573","DOIUrl":"https://doi.org/10.1145/3284566.3284573","url":null,"abstract":"With the exponential growth of smartphone usage and its computational capability, there is an opportunity today to build a usable navigation system for the visually impaired. A smartphone contains many sensors for sensing the surrounding environment such as GPS, cameras, and inertial sensors. However, there are many challenges for building a navigation system, such as low-level methods of environment sensing, accuracy, and efficient data processing. In this paper, we address some of these challenges and present a system for traffic light detection, which is fundamental for pedestrian navigation by the visually impaired in outdoors. In this system, we analyze the video feed from a smartphone's camera using model-based computer vision techniques to detect traffic lights. Specifically, we utilize both color and shape information as they are the most prominent features of the traffic lights. Additionally, we use the inertial sensors of a smartphone to compute the 3D orientation of a smartphone to predict a segment of a video frame, which is highly probable to contain the traffic lights. By processing only that segment, we improve the computational time by an order of magnitude on average. We evaluated this system in various lighting conditions such as cloudy, sunny, and at night, and achieved over 96% accuracy in the traffic light detection and recognition.","PeriodicalId":280468,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124168683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Analysis, Integration and Visualization of Urban Data From Multiple Heterogeneous Sources 多异构城市数据分析、集成与可视化

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284569

Pedro Magalhães Fortini, C. Davis

{"title":"Analysis, Integration and Visualization of Urban Data From Multiple Heterogeneous Sources","authors":"Pedro Magalhães Fortini, C. Davis","doi":"10.1145/3284566.3284569","DOIUrl":"https://doi.org/10.1145/3284566.3284569","url":null,"abstract":"The rapid progress of urbanization creates great challenges for urban planners. These challenges include the environment, energy consumption, transport, and other areas. The massive amount of information generated everyday in urban environments allows more precise diagnostics of the problems and helps in the design of solutions. Since such sources of information are heterogeneous and involve a large amount of data, major computational challenges arise. The objective of this work is to propose techniques and methods that allow the integration and visualization of urban data from multiple heterogeneous sources, aiming to create tools for urban data analysis, focusing mainly on transportation and transit. We propose the Urban Transit Fingerprint visualization, in which the geometry, length and duration of travels within a city can be compared, and indicators of the relative efficiency between private (individual) and public (mass) transport can be assessed. Data from Belo Horizonte and São Paulo, Brazil, are analyzed using the proposed technique as case studies. Results show wide discrepancies in the effort a public transit user has to make for her mobility in various regions of each city, as compared with individual travel. These results help explaining the sharp drop in the number of transit users over the last years, thus calling on urban planners to devise public policies in the search for better solutions.","PeriodicalId":280468,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125636966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Aging in Place: Challenges for Smart & Resilient Communities 老龄化:智能和弹性社区的挑战

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284567

Mark McKenney, Connie Frey-Spurlock

引用次数: 3

SCOUTS 童子军

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284570

N. Tonekaboni, Lakshmish Ramaswamy, Deepak R. Mishra, A. Grundstein, Sujeet Kulkarni, Yanzhe Yin

引用次数: 1

Multiple Evaluation in the Future Population Distribution for Sustainable City 可持续城市未来人口分布的多重评价

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566.3284568

Shota Tamura, Takahiro Tanaka

{"title":"Multiple Evaluation in the Future Population Distribution for Sustainable City","authors":"Shota Tamura, Takahiro Tanaka","doi":"10.1145/3284566.3284568","DOIUrl":"https://doi.org/10.1145/3284566.3284568","url":null,"abstract":"Recent years have seen a decrease in the population of Japan. If urban areas continue to expand to the suburbs with this depopulation, various urban problems will arise including difficulty of maintaining public transport system and increase in energy consumption. To address this, compact urban structure is proposed, corresponding to the decreasing population. Actually, Japanese government announced, in 2014 guideline and policy for compact city. This encourages local governments to decide \"inducing area for urban functions\" in which urban functions should be concentrated and \"inducing area for dwelling\" that should attract residents. However, it is not clear where these areas should be located. It is important to examine the positive and negative zone for living in term of various perspectives and future urban structure should be designed based on the evaluations. This study aims to examine the high potential area for living in term of six viewpoints such as public transport convenience, disaster risk, environmental load, infrastructure cost, economy and convenience of welfare and medical facilities and create scenarios by concentrating population to efficient zones classified by cluster analysis with evaluation data. Finally, the scenarios are evaluated in the same method and compared to assess the impact of compaction on some indexes and differences from BAU. Results show that cluster 2 zones (around the inside of urbanization areas) are higher positive potential in all indexes. The scenario compacted based on all evaluations is more efficient in all aspects than BAU. However, other scenario compacted based on one criterion has tradeoff between other indexes.","PeriodicalId":280468,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129227431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities 第一届美国计算机学会sigspace弹性和智慧城市研讨会论文集

Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities Pub Date : 2018-11-06 DOI: 10.1145/3284566

引用次数: 0