Course title
都市空間情報学特論Ⅰ   [Advanced Topics on Urban Space Informatics Ⅰ]
Course category	common courses	Requirement		Credit	2
Department		Year	～	Semester	1st
Course type	1st	Course code	1060717
Instructor(s)
幸島 明男, 清水 郁子   [SASHIMA Akio, SHIMIZU Ikuko]
Facility affiliation	Graduate School of Engineering	Office		Email address

Course description

In this lecture, we present a future image of urban and social information services based on integrated information processing of real world information brought by sensory data and one from cyber space. In order to understand the real world situation in cyber space, we need 1) to recognize and learn about real world situation by referring physical and mathematical models by which real world can be explained, 2) to construct models of real world in cyber space, and 3) to execute urban and social services based on the constructed models. While presenting the new images of urban and social services, we also address the key technologies used to implement such the services and the ways of integration of the technologies including information service implementation, sensing, physical and mathematical model, recognition and machine learning of sensory data

Expected Learning

First goal of attendee of this lecture is to acquire the sense of “information architect” who can design and show the way of complex and innovative information service implementaiton. Second goal is to deeply learn key technologies, although it is not required to understand the details of all the technologies addressed in the lecture, because wide variety of technologies are talked in the lecture.

Course schedule

We present the image of the following urban and social services, and the ways and methods of integrating the key technologies. [Service] Introduction to implementation of urban and social services Understanding and visualization of urban spaces Understanding human behavior and vital signals Efficient distribution of social common resources based on information sharing by information technology Control of human flow in large-scale social event and safety [Key Technology] Machin learning, Deep Learning Complex network as social model Mathematical model of social resource distribution, percolation theory Information architecture of sensory data processing Simulation of human and traffic flow

Prerequisites

Knowledge on programming, information network, physics, and mathematics at the graduate level of science or engineering faculty is required. You should prepare and review the contents of this lecture in addition to the standard hours (30 hours) of lectures, using teaching materials and reference books.

Required Text(s) and Materials

Specified in the lecture, if needed.

References

Assessment/Grading

Attendance ratio, and document report.

Message from instructor(s)

Not just learn, try to implement innovative urban and social information services.

Course keywords

Urban service, social service, vital information, recognition, machine learning, complex network, percolation, simulation.

Office hours

Remarks 1

Remarks 2

Related URL

Lecture Language

Language Subject

Last update

2/19/2022 10:51:14 AM