Next Article in Journal
Real-Time Hybrid Multi-Sensor Fusion Framework for Perception in Autonomous Vehicles
Previous Article in Journal
Quantitative Analysis of Soil Total Nitrogen Using Hyperspectral Imaging Technology with Extreme Learning Machine
Previous Article in Special Issue
Analysis of the Influence of Different Settings of Scan Sequence Parameters on Vibration and Noise Generated in the Open-Air MRI Scanning Area
Open AccessArticle

Real-Time Human-In-The-Loop Simulation with Mobile Agents, Chat Bots, and Crowd Sensing for Smart Cities

by Stefan Bosse 1,* and Uwe Engel 2
1
Faculty Computer Science, University of Koblenz-Landau, 56070 Koblenz, Germany
2
Department of Social Science, University of Bremen, 28359 Bremen, Germany
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(20), 4356; https://doi.org/10.3390/s19204356
Received: 7 August 2019 / Revised: 25 September 2019 / Accepted: 1 October 2019 / Published: 9 October 2019
Modelling and simulation of social interaction and networks are of high interest in multiple disciplines and fields of application ranging from fundamental social sciences to smart city management. Future smart city infrastructures and management are characterised by adaptive and self-organising control using real-world sensor data. In this work, humans are considered as sensors. Virtual worlds, e.g., simulations and games, are commonly closed and rely on artificial social behaviour and synthetic sensor information generated by the simulator program or using data collected off-line by surveys. In contrast, real worlds have a higher diversity. Agent-based modelling relies on parameterised models. The selection of suitable parameter sets is crucial to match real-world behaviour. In this work, a framework combining agent-based simulation with crowd sensing and social data mining using mobile agents is introduced. The crowd sensing via chat bots creates augmented virtuality and reality by augmenting the simulated worlds with real-world interaction and vice versa. The simulated world interacts with real-world environments, humans, machines, and other virtual worlds in real-time. Among the mining of physical sensors (e.g., temperature, motion, position, and light) of mobile devices like smartphones, mobile agents can perform crowd sensing by participating in question–answer dialogues via a chat blog (provided by smartphone Apps or integrated into WEB pages and social media). Additionally, mobile agents can act as virtual sensors (offering data exchanged with other agents) and create a bridge between virtual and real worlds. The ubiquitous usage of digital social media has relevant impact on social interaction, mobility, and opinion-making, which has to be considered. Three different use-cases demonstrate the suitability of augmented agent-based simulation for social network analysis using parameterised behavioural models and mobile agent-based crowd sensing. This paper gives a rigorous overview and introduction of the challenges and methodologies used to study and control large-scale and complex socio-technical systems using agent-based methods. View Full-Text
Keywords: simulation; agent-based modelling; mobile agents; crowd sensing; smart traffic control; social interaction simulation; agent-based modelling; mobile agents; crowd sensing; smart traffic control; social interaction
Show Figures

Figure 1

MDPI and ACS Style

Bosse, S.; Engel, U. Real-Time Human-In-The-Loop Simulation with Mobile Agents, Chat Bots, and Crowd Sensing for Smart Cities. Sensors 2019, 19, 4356.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop