Context-Aware Android Applications through Transportation Mode Detection Techniques

In this paper, we study the problem of how to detect the current transportation mode of the user from the smartphone sensors data, because this issue is considered crucial for the deployment of a multitude of mobility-aware systems, ranging from trace collectors to health monitoring and urban sensing systems. Although some feasibility studies have been performed in the literature, most of the proposed systems rely on the utilization of the GPS and on computational expensive algorithms that do not take into account the limited resources of mobile phones. On the opposite, this paper focuses on the design and implementation of a feasible and efficient detection system that takes into account both the issues of accuracy of classification and of energy consumption. To this purpose, we propose the utilization of embedded sensor data (accelerometer/gyroscope) with a novel meta-classifier based on a cascading technique, and we show that our combined approach can provide similar performance than a GPS-based classifier, but introducing also the possibility to control the computational load based on requested confidence. We describe the implementation of the proposed system into an Android framework that can be leveraged by third-part mobile applications to access context-aware information in a transparent way

Assessing the First and Last Mile Problem in Intercity Passenger Rail: Effects on Mode Choice and Trip Frequency

Passenger rail service is an integral part of intercity transportation networks, especially in areas where residents do not have access to cars or other intercity travel options. Some municipalities in the U.S. have experienced a decline in passenger rail service in recent years, which has prompted schedule reductions and entire abandonment of service in some cases. To improve the current intercity passenger rail service predicament, two alternatives can be considered: (1) improve the rail service itself (frequency, infrastructure, etc.) and (2) improve accessibility to the rail stations, which might be cheaper and more cost-effective overall. Improvements in accessibility can impact a wider area and play a key role in passengers choosing rail service as their travel alternative. To address the above issues, the main objective of this thesis was to explore the possibilities for enhancing access to medium distance travel which is, according to the U.S. Bureau of Transportation Services (BTS), between three to five hours or more than 50 miles of travel from home to the nearest intercity passenger rail station. The approach of this thesis was to identify the factors that affect mode choice and level of usage in order to subsequently evaluate different strategies for passengers to reach a station. The Hoosier State Train (HST), a short-distance intercity passenger rail system that travels between Chicago and Indianapolis four days a week, was chosen as a case study. HST has four intermediate stops in Indiana. For some of those intermediate stops, HST is the only intercity public transit service offered to reach either Chicago or Indianapolis. An HST on-board survey that explored opportunities to increase the HST ridership was conducted in November and December of 2016. The survey findings indicated that there are passengers who travel from counties farther away from a county with a station to take the train. Moreover, it was found that most of the respondents drove a personal vehicle, rented a car, or were dropped off to reach a train station in Indiana. The first and last mile (FMLM) of a trip is commonly used to describe passenger travel as far as getting to/from transit stops/stations. The findings of this thesis suggest that there is a gap in the FMLM for intercity rail passengers. Solving the FMLM problem would extend access to transportation systems and could increase the number of passengers from remote communities, such as rural areas. The FMLM problem has been addressed in different public transit contexts, mainly within urban areas; however, limited research efforts have been undertaken to examine the FMLM problem of intercity passenger rail. This thesis intends to fill this gap by exploring the best strategies to address the FMLM problem of short distance intercity passenger rail (i.e., corridors that are less than 750 miles long according to the Passenger Rail Improvement and Investment Act, 2008). Using the data collected on board the HST in Indiana, this thesis estimated a multi-attribute attitude model (MAM) to assess how transportation mode preferences for intercity travel are made and how the factors considered in mode choice decisions vary among individuals with different levels of access to an intercity passenger rail line. An ordered probit model was estimated to further investigate how passenger characteristics, as well as the factors associated with both access to a rail station and mode choice decisions, relate to the frequency of travel by intercity rail. This thesis also presents the results of an accessibility analysis conducted for the state of Indiana in order to identify the areas in need of FMLM service where no public transportation services exist and the cost of reaching a station from a desired origin is expensive. To that end, a cost survey for the different modes available was conducted to determine the average travel cost to the nearest station. The analysis was carried out in ArcGIS using origin-destination information from the on-board survey, transportation network information from the U.S. BTS, and general transit feed specification data. The results of this thesis can assist Amtrak and state transportation agencies identify which aspects of rail service potentially can be enhanced to attract more passengers as well as promote the use of intercity passenger rail service in the U.S. Additionally, the findings could have extensive implications for planning strategies to provide access to passenger rail stations. While the inferences in this thesis are case-study specific for Indiana, the proposed methodology could be used to identify areas where accessibility can be improved in other U.S. states or countries with similar characteristics

Sensor deployment for air pollution monitoring using public transportation system

IEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012 hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)Air pollution monitoring is a very popular research topic and many monitoring systems have been developed. In this paper, we formulate the Bus Sensor Deployment Problem (BSDP) to select the bus routes on which sensors are deployed, and we use Chemical Reaction Optimization (CRO) to solve BSDP. CRO is a recently proposed metaheuristic designed to solve a wide range of optimization problems. Using the real world data, namely Hong Kong Island bus route data, we perform a series of simulations and the results show that CRO is capable of solving this optimization problem efficiently. © 2012 IEEE.published_or_final_versio

A Modular Deep Learning Framework for Scene Understanding in Augmented Reality Applications

Taking as input natural images and videos augmented reality (AR) applications aim to enhance the real world with superimposed digital contents enabling interaction between the user and the environment. One important step in this process is automatic scene analysis and understanding that should be performed both in real time and with a good level of object recognition accuracy. In this work an end-to-end framework based on the combination of a Super Resolution network with a detection and recognition deep network has been proposed to increase performance and lower processing time. This novel approach has been evaluated on two different datasets: the popular COCO dataset whose real images are used for benchmarking many different computer vision tasks, and a generated dataset with synthetic images recreating a variety of environmental, lighting and acquisition conditions. The evaluation analysis is focused on small objects, which are more challenging to be correctly detected and recognised. The results show that the Average Precision is higher for smaller and low resolution objects for the proposed end-to-end approach in most of the selected conditions

FATHER: FActory on THE Road

In most factories today the robotic cells are deployed on well enforced bases to avoid any external impact on the accuracy of production. In contrast to that, we evaluate a futuristic concept where the whole robotic cell could work in a moving platform. Imagine a trailer of a truck moving along the motorway while exposed to heavy physical impacts due to maneuvering. The key question here is how the robotic cell behaves and how the productivity is affected. We propose a system architecture (FATHER) and show some solutions including network related information and artificial intelligence to make the proposed futuristic concept feasible to implement.Comment: In Proc., 35th European Simulation and Modelling Conference, Oct 27-29, 202

Delay-Tolerant, Low-Power Protocols for Large Security-Critical Wireless Sensor Networks

This paper reports the analysis, implementation, and experimental testing of a delay-tolerant and energy-aware protocol for a wireless sensor node, oriented to security applications. The solution proposed takes advantages from different domains considering as a guideline the low power consumption and facing the problems of seamless and lossy connectivity offered by the wireless medium along with very limited resources offered by a wireless network node. The paper is organized as follows: first we give an overview on delay-tolerant wireless sensor networking (DTN); then we perform a simulation-based comparative analysis of state-of-the-art DTN approaches and illustrate the improvement offered by the proposed protocol; finally we present experimental data gathered from the implementation of the proposed protocol on a proprietary hardware node

Determining a Waste Tyre Management System for Hong Kong

Twenty-five percent of waste tires in Hong Kong are not recycled in spite of a vigorous recycling industry and landfills nearing capacity. The goal of this project was to identify possible solutions to the country\u27s waste tire management. To accomplish this goal, we interviewed influential members of the waste tire community, conducted library research, and researched current waste tire statistics. Through analysis of this data we developed a set of recommendations for Hong Kong to accomplish complete waste tire recycling

147th municipal government report, fiscal year July 1, 1999-June 30, 2000.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire

A study on the effectiveness of new applications by providing up-to-date real time information guide for user of GoKL city bus / Nor Hasliny Rusli

Public transportation services are basic facilities provided by governments of certain countries to their citizens. With the existence of public transportation services, it may helped them to travel from one place to another conveniently. This research focuses on tourists using the ‘GoKL City Bus’ service in Kuala Lumpur City, to travel places of interest free of charge and free from unnecessary hassle. The outcome is the hoped that the government will promote tourism in a better way and at the same time it will determine the effectiveness of a new Mobile Application model that is to be introduced in near future. This research was done manually by distributing survey questionnaires to around 50 respondents. The findings of this research will be used to develop the new mobile application for tourists to easily find and locate food courts, entertainments, shopping complexes, leisure centres and other attractions nearby. Hopefully, this research will be able to improve public transportation services and tourism in Malaysia besides promoting the use of this mobile application