2016年智能城市的人群智力国际研讨会 The international Workshop on Crowd Intelligence for Smart Cities CISC 2016

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活动简介

Cities are experiencing significant challenges in many aspects such as efficient energy management, economic growth and development, security and quality of life of their citizens. In the era of big data, mobile internet and cloud computing, we are now provided with good opportunities to leverage the crowd intelligence to better sense and manage the city. The meaning of the word “crowd” is mainly two-fold, in terms of the data collection and fusion.

From the perspective of data collection, participatory sensing (people-centric sensing/mobile crowdsensing) presents a new paradigm based on the power of mobile devices. The sheer number of user-companioned devices, including mobile phones, wearable devices, and smart vehicles, and their inherent mobility enables that we can acquire local knowledge (e.g., location, personal and surrounding context, noise level, traffic conditions) through sensor-enhanced mobile devices.
From the perspective of data fusion, a variety of open datasets from multiple domains are available nowadays, from social media to public transportation, from health care to wireless communication networks. When addressing a specific problem in smart cities, we usually need to harness multiple disparate datasets. For example, to create a fine-grained air pollution monitoring map in a city, we need to explore air quality data reported by monitor stations, together with meteorological data, emissions from vehicles and factories, as well as the dispersion condition of a place.

The objective of the CISC 2016 is to bring together researchers and practitioners both from academia and industries with the goal to discuss, identify and share experiences surrounding construction of smart city systems, city context analysis, its applications and deployment experiences based on the crowd intelligence. We hope that the workshop will contribute to establish a research community in the smart city research area with a focus on the crowd intelligence. The expected outcomes are:

Survey of the state-of-the-art smart city technologies based on crowd intelligence – systems, middleware and data collection/analysis method.
Sharing the knowledge and experiences of practical smart city projects/challenges, or novel and interesting ideas. This includes various crowd-based applications and use cases.
The future direction of the smart city research from the point of view of the data collection and fusion in diverse domains.

征稿信息

重要日期

2016-05-11

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征稿范围

Smart City Big Data Collection and Analysis

New types of data collection and analysis technologies/methodologies are required to create people/citizen-centric services. Specifically, not only the existing mobile crowdsensing, participatory sensing and opportunistic sensing, but also other types of new sensing approaches are welcomed to be submitted to this workshop.

Crowd Intelligence based Smart City Systems, Middleware and Framework

Smart city applications based on crowd intelligence need to be validated in real-world environments. The workshop invites papers sharing results of smart city applications and experimentations performed in lab and at city scale, in particular with data collected from multiple domains or participants.

Crowd Intelligence based Smart City Application

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Security, Trust, and Privacy Issues in Crowd Intelligence

As crowd intelligence aggregates huge amount of people generated data, it will face serious concerns in terms of security, trust, and privacy. This workshop thus expects the papers to propose secure, reliable and privacy-preserving crowd intelligence technologies and applications for smart cities.

Incentive Mechanism for Crowd Intelligence based Smart City Applications

The extensive participation is the key factor for the success of crowd intelligence based smart city applications. To encourage the wide participation of citizens to contribute their data, information or knowledge about the city they live in, it is crucial to study corresponding incentive mechanisms, which the workshop also focuses on.

Missing Data Inference Techniques in Smart Cities

Due to the limited incentive budget and/or human mobility patterns, the participants involved in the crowd intelligence applications may not be able to cover every region of the city. This workshop also calls for the papers discussing advanced data inference techniques for estimating the missing data of uncovered regions to obtain an overall view of the whole city.

Optimizing Crowd Intelligence based Systems for Smart Cities

Given the incentive mechanisms, data quality metrics, missing data treatments as well as the limited budget, a crowd intelligence based system should be optimized to achieve its best performance. This workshop also calls for the paper discussing the novel optimization problems, such as multi-objective optimization for multi-task crowd sensing, and bandit optimization in online crowd sensing.