Multimodal Classification of Urban Micro-Events

In this paper we seek methods to effectively detect urban micro-events. Urban micro-events are events which occur in cities, have limited geographical coverage and typically affect only a small group of citizens. Because of their scale these are difficult to identify in most data sources. However, by using citizen sensing to gather data, detecting them becomes feasible. The data gathered by citizen sensing is often multimodal and, as a consequence, the information required to detect urban micro-events is distributed over multiple modalities. This makes it essential to have a classifier capable of combining them. In this paper we explore several methods of creating such a classifier, including early, late, hybrid fusion and representation learning using multimodal graphs. We evaluate performance on a real world dataset obtained from a live citizen reporting system. We show that a multimodal approach yields higher performance than unimodal alternatives. Furthermore, we demonstrate that our hybrid combination of early and late fusion with multimodal embeddings performs best in classification of urban micro-events

The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm

This paper is motivated by the concept that the successful, effective, and sustainable implementation of the smart city paradigm requires a close cooperation among researchers with different, complementary interests and, in most cases, a multidisciplinary approach. It first briefly discusses how such a multidisciplinary methodology, transversal to various disciplines such as architecture, computer science, civil engineering, electrical, electronic and telecommunication engineering, social science and behavioral science, etc., can be successfully employed for the development of suitable modeling tools and real solutions of such sociotechnical systems. Then, the paper presents some pilot projects accomplished by the authors within the framework of some major European Union (EU) and national research programs, also involving the Bologna municipality and some of the key players of the smart city industry. Each project, characterized by different and complementary approaches/modeling tools, is illustrated along with the relevant contextualization and the advancements with respect to the state of the art

From Field to Virtual: Developing Hybrid-Learning Media of Earthquake and Tsunami Disaster Resilience Strategy of Fishing Village Community in Bandar Lampung

Indonesia is an earthquake and tsunami prone area, therefor, disaster resilience strategy is important for surviving and living. The topic of disaster resilience strategy of earthquake and tsunami and case study at Kangkung village in Bandar Lampung then become a topic of hybrid-learning for students with videos as media. It brings a case study of earthquake and tsunami disaster resilience strategy from field to the class by virtual learning media. The research conducted by mix method of (1) Fieldwork approach; (2) Hybrid-learning media production; and (3) Qualitative approach. Fieldwork conducted by observation and documentation (pictures and movies) of Kangkung fishing village community in Bandar Lampung while qualitative approach conducted by questionnaires and in-depth interview to students of Department of Infrastructure and Environmental Engineering, Soegijapranata Catholic University. The results have been analyzed by scoring method. Several conclusions can be described as: (1) five aspects of attractiveness, delivery, learning atmosphere, understanding, and motivation inflicted, can be applied in scoring method; and (2) hybrid-learning media is very good to implemented to learn disaster resilience strategy of earthquake and tsunami at Kangkung fishing village in Bandar Lampung