Peaceful and Secure Cities

Due to the explosive increase per capita in vehicle ownership in China brought about by the continuous development of the economy and society, many negative impacts have arisen, making it necessary to establish the smart city system that has rapidly developing vehicle detection technology as its data acquisition system. This paper proposes a lightweight detection model based on an improved version of YOLOv5 to address the problem of missed and false detections caused by occlusion during rush hour vehicle detection in surveillance videos. The proposed model replaces the BottleneckCSP structure with the Ghostnet structure and prunes the network model to speed up inference. Additionally, the Coordinate Attention Mechanism is introduced to enhance the network’s feature extraction and improve its detection and recognition ability. Distance-IoU Non-Maximum Suppression replaces Non-Maximum Suppression to address the issue of false detection and omission when detecting congested targets. Lastly, the combination of the five-frame differential method with VIBE and MD-SILBP operators is used to enhance the model’s feature extraction capabilities for vehicle contours. The experimental results show that the proposed model outperforms the original model in terms of the number of parameters, inference ability, and accuracy when applied to both the expanded UA-DETRAC and a self-built dataset. Thus, this method has significant industrial value in intelligent traffic systems and can effectively improve vehicle detection indicators in traffic monitoring scenarios. Full article

Current awareness of epidemic threats and critical experiences of the COVID-19 pandemic require extension of the management model in the smart city, especially in the field of mobility and transport services, with monitoring of epidemic hazards. This paper addresses the issue of epidemic hazards, a new challenge in smart cities, and customer delivery services. The novel DHI methodology for epidemic hazards assessment is presented and applied to compare customer delivery services in aspects of SARS-CoV-2 epidemic hazards. The case studies presented a detailed analysis of epidemic hazards on the basis of process algorithms and dedicated quantitative scales to assess factors influencing the mechanisms of virus transmission. The developed DHI methodology and the results obtained for transport services constitute important cognitive knowledge for the administrative personnel in smart city. Full article

There are many options and factors in the production phase of housing. In the marketing phase, houses are presented to the customer’s taste. Therefore, it is clear that a customer-oriented approach is necessary to establish a supply–demand balance in housing production on the basis of quality. This study aimed to determine customers’ housing demands in the construction sector. Within the scope of the study, 303 surveys were conducted in 30 different provinces of Turkey. The data obtained were analyzed by WEKA software with association rule extraction as the data mining method. The distribution of other attributes was determined according to two different class labels, namely the ownership status of the houses (tenant or homeowner) and customers’ expectations of the houses. As a result of the study, it is clear that people living in Turkey prefer a south-facing facade when purchasing a house. In addition, it is seen that the property owners demand 4 + 1 independent units. It is remarkable that individuals who are tenants want the living room to be spacious. The results of the study also revealed that female individuals have higher expectations of housing than male individuals. At the same time, it is understood that people’s expectations of housing differ according to the variables of age, education level, and the number of family members. The majority of the results in this study had a confidence value of 90% and above. This study was intended to serve as a guide for housing developers in Turkey to better understand and meet the demands of buildings’ residents. Full article

Falling objects from façades often lead to serious accidents, which has become a technical problem to be solved urgently. This paper established a database of potential safety hazard of falling objects from façades via the statistics of detection façades in Shanghai. Some detailed insufficiencies and swelling defects were analyzed. A risk assessment system of falling objects from façades was established using the Fault Tree Analysis (FTA) method. The weight coefficient was determined by the Analytic Hierarchy Process (AHP). The beta distribution was used to fit the probability distribution of the occurrence probability of the elementary risk event. Based on the Monte Carlo model, the risk of falling objects from façades was assessed. A probability distribution of the risk probability of falling objects from façades and the importance of elementary risk factors were obtained. Some risk control measures of falling objects from façades were proposed. Full article

The increasing number of crimes affecting urban areas requires the adoption of countermeasures to tackle this problem from different perspectives, including the technological one. Currently, there are many research initiatives with the goal of applying machine or deep learning techniques leveraging historical data to predict the occurrence of crime incidents. Conversely, there is a lack of tools aiming at crime risk assessment, in particular, by supporting the police in conceiving what could be the crime incidents affecting a given city area. To this purpose, we propose the Crime Prevention System, a modular software application for qualitative crime risk assessment. This consists of an ontology of crime risk, a module to retrieve contextual data from OpenStreetMap, semantics reasoning functionalities, and a GIS interface. We discuss how this system can be used through a case study related to the Italian city of Syracuse. Full article

In order to cope with limited land availability and the increasing urban population, more high-rise buildings are being built throughout cities, but this has also led to new challenges in the emergency evacuation of people. Therefore, we conducted an evacuation experiment of a group of people in the stairwells of high-rise buildings to explore the movement law of groups in stairwells. The experiment had 18 scenes, including the evacuation movement of an independent group and the crowd evacuation movement of different groups. Analyzing the independent groups’ movement showed that regardless of the type of group, the average speed of the crowd was more than 1.2 m/s, which was longer than that of previous studies. The more constraints in the evacuation process, the smaller the speed difference between males and females. Group cohesion was mostly concentrated at about 1 s. Moreover, group velocity and cohesion were found to have no significant correlation in stairwell movement. Analyzing the crowd evacuation time of eight different scenes showed that it took longer for crowds bearing weight to evacuate than those not bearing weight. According to the spatiotemporal evolution of crowd evacuation in stairwells, the crowd moves intermittently in the evacuation process, especially in the early and middle stages of evacuation, and the influence of group factors on this process was not obvious. Regardless of the kind of scene or stairwell, the number of pedestrians generally first increased and then decreased to a significantly low value, and the number of pedestrians reached about 30 in the scenario of people without any load. Additionally, the speed of the pedestrians entering the stairwell in the back of the group was not faster than that of the pedestrians in the front, which showed that pedestrians rarely engaged in overtaking behavior. The research results of this paper not only enrich evacuation research but also provide support for the design of high-rise stairs. Full article