Risk management in solitary agricultural work: new technologies for handling emergency and falls from great heights (SHADE)

Solitary work and agricultural activities are the scenarios of a large number of severe injuries and deaths, also because first aid may be difficult to achieve in isolated locations. This work proposes a technology available on smartphones that allows triggering an emergency call when a fall from height or an unconsciousness state is detected. The results of several tests, which include different detection algorithms and scenarios, are reported in this work. Tests performed with the aid of a dummy have allowed developing a reliable algorithm for the detection of dangerous situations. This system is available as an Android application

Risk management in solitary agricultural work: new technologies for handling emergency and falls from great heights (SHADE)

Solitary work and agricultural activities are the scenarios of a large number of severe injuries and deaths, also because first aid may be difficult to achieve in isolated locations. This work proposes a technology available on smartphones that allows triggering an emergency call when a fall from height or an unconsciousness state is detected. The results of several tests, which include different detection algorithms and scenarios, are reported in this work. Tests performed with the aid of a dummy have allowed developing a reliable algorithm for the detection of dangerous situations. This system is available as an Android application

Fatalities resulting from falls from height in agricultural contexts

Agricultural work encompasses a variety of activities which carry with them different risks. One such activity is working at height, a frequent cause of fatal accidents. The aim of this work is to describe and discuss a typical case of a fall from height in order to understand the traumatic consequences of such accidents, to analyze the dynamics and lesions, and highlight the dangers of working at height. These falls, which may involve farm workers who are officially or unofficially employed, can produce injuries whose seriousness is not always strictly correlated to the height of the fal

Three dimensional visualisation of Port Dickson Polytechnic campus in cityengine web viewer

Development of modern technology and its ability to store, process and supply of digital data has led to a demand for three dimensional (3D) modeling of virtual campus has increased dramatically. Of late, many educational institutes have developed their own campus geodatabase in 3D environment. In this research, the emphasis is given on the development of the 3D building model campus using close range photogrammetry approach due to high cost of data acquisition techniques using airbone laser scanning, terrestrial laser scanning techniques and availability of data. Thus, the close range photogrammetry technique has been selected due to low cost method for data acquisition through capturing the selected building photographs using digital camera. In order to develop the 3D building models, six buildings with different architectural designs and geometries in Port Dickson Polytechnic campus have been chosen as prototype which are modelled using close range photogrammtry approach. The photographs of buildings are then processed using PhotoModeler software to produce the 3D building models in the level of detail (LoD) 2. The building models are textured with the real photographs taken from the field while the roof of the buildings are edited using the SketchUp software. The building models are also georeferenced to the real world coordinate system based on the geocentric Rectified Skew Orthomorphic (RSO) coordinate system. Due to the lack of information access on the web in 3D, CityEngine Web Viewer is used for 3D visualisation of the building models and supported features are also be added to create a realistic model of 3D virtual campus. Through the viewer, the users are able to navigate the 3D building models, zooming and performing the spatial query to extract the information of the buildings. The accuracy of 3D buildings models are evaluated and determined based on the visual analyses and quantitative analyses. At the end of the research, the 3D buildings models can be visualised in the LoD 2

An efficient MapReduce-based parallel clustering algorithm for distributed traffic subarea division

Traffic subarea division is vital for traffic system management and traffic network analysis in intelligent transportation systems (ITSs). Since existing methods may not be suitable for big traffic data processing, this paper presents a MapReduce-based Parallel Three-Phase K -Means (Par3PKM) algorithm for solving traffic subarea division problem on a widely adopted Hadoop distributed computing platform. Specifically, we first modify the distance metric and initialization strategy of K -Means and then employ a MapReduce paradigm to redesign the optimized K -Means algorithm for parallel clustering of large-scale taxi trajectories. Moreover, we propose a boundary identifying method to connect the borders of clustering results for each cluster. Finally, we divide traffic subarea of Beijing based on real-world trajectory data sets generated by 12,000 taxis in a period of one month using the proposed approach. Experimental evaluation results indicate that when compared with K -Means, Par2PK-Means, and ParCLARA, Par3PKM achieves higher efficiency, more accuracy, and better scalability and can effectively divide traffic subarea with big taxi trajectory data

Combining SysML and Timed Coloured Petri Nets for Designing Smart City Applications

A smart city is an urban centre that integrates a variety of solutions to improve infrastructure performance and achieve sustainable urban development. Urban roads are a crucial infrastructure highly demanded by citizens and organisations interested in their deployment, performance, and safety. Urban traffic signal control is an important and challenging real-world problem that aims to monitor and improve traffic congestion. The deployment of traffic signals for vehicles or pedestrians at an intersection is a complex activity that changes constantly, so it is necessary to establish rules to control the flow of vehicles and pedestrians. Thus, this article describes the joint use of the SmartCitySysML, a profile proposed by the authors, with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams specifying the internal behaviour, and then verify the developed model to prove behavioural properties of an urban traffic signal control system

Contextualized property market models vs. Generalized mass appraisals: An innovative approach

The present research takes into account the current and widespread need for rational valuation methodologies, able to correctly interpret the available market data. An innovative automated valuation model has been simultaneously implemented to three Italian study samples, each one constituted by two-hundred residential units sold in the years 2016-2017. The ability to generate a "unique" functional form for the three different territorial contexts considered, in which the relationships between the influencing factors and the selling prices are specified by different multiplicative coefficients that appropriately represent the market phenomena of each case study analyzed, is the main contribution of the proposed methodology. The method can provide support for private operators in the assessment of the territorial investment conveniences and for the public entities in the decisional phases regarding future tax and urban planning policies