801 research outputs found
Using a mobile robot for hazardous substances detection in a factory environment
Dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáIndustries that work with toxic materials need extensive security protocols to avoid accidents.
Instead of having fixed sensors, the concept of assembling the sensors on a mobile
robot that performs the scanning through a defined path is cheaper, configurable and
adaptable. This work describes a mobile robot, equipped with several gas sensors and
LIDAR, that follows a trajectory based on waypoints, simulating a working Autonomous
Guided Vehicle (AGV). At the same time, the robot keeps measuring for toxic gases. In
other words, the robot follows the trajectory while the gas concentration is under a defined
value. Otherwise, it starts the autonomous leakage search based on a search algorithm
that allows to find the leakage position avoiding obstacles in real time. The proposed
methodology is verified in simulation based on a model of the real robot. Therefore, three
path plannings were developed and their performance compared. A Light Detection And
Ranging (LIDAR) device was integrated with the path planning to propose an obstacle
avoidance system with a dilation technique to enlarge the obstacles, thus, considering the
robot’s dimensions. Moreover, if needed, the robot can be remotely operated with visual
feedback. In addition, a controller was made for the robot. Gas sensors were embedded in
the robot with Finite Impulse Response (FIR) filter to process the data. A low cost AGV
was developed to compete in Festival Nacional de RobĂłtica (Portuguese Robotics Open)
2019 - Gondomar, describing the robot’s control and software solution to the competition.As indústrias que trabalham com materiais tóxicos necessitam de extensos protocolos
de segurança para evitar acidentes. Ao invés de ter sensores estáticos, o conceito de
instalar sensores em um robô móvel que inspeciona através de um caminho definido é mais
barato, configurável e adaptável. O presente trabalho descreve um robô móvel, equipado
com vários sensores de gás e LIDAR, que percorre uma trajetória baseada em pontos
de controle, simulando um AGV em trabalho. Em simultâneo são efetuadas medidas de
gases tóxicos. Em outras palavras, o robô segue uma trajetória enquanto a concentração
de gás está abaixo de um valor definido. Caso contrário, inicia uma busca autônoma
de vazamento de gás com um algoritmo de busca que permite achar a posição do gás
evitando os obstáculos em tempo real. A metodologia proposta é verificada em simulação.
TrĂŞs algoritmos de planejamento de caminho foram desenvolvidos e suas performances
comparadas. Um LIDAR foi integrado com o planejamento de caminho para propĂ´r
um sistema de evitar obstáculos. Além disso, o robô pode ser operado remotamente com
auxĂlio visual. Foi feito um controlador para o robĂ´. Sensores de gás foram embarcados no
robĂ´ com um filtro de resposta ao impulso finita para processar as informações. Um veĂculo
guiado automático de baixo custo foi desenvolvido para competir no Festival Nacional de
RobĂłtica 2019 - Gondomar. O controle do veĂculo foi descrito com o programa de solução
para a competição
Semantic discovery and reuse of business process patterns
Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse
Latitude, longitude, and beyond:mining mobile objects' behavior
Rapid advancements in Micro-Electro-Mechanical Systems (MEMS), and wireless communications, have resulted in a surge in data generation. Mobility data is one of the various forms of data, which are ubiquitously collected by different location sensing devices. Extensive knowledge about the behavior of humans and wildlife is buried in raw mobility data. This knowledge can be used for realizing numerous viable applications ranging from wildlife movement analysis, to various location-based recommendation systems, urban planning, and disaster relief. With respect to what mentioned above, in this thesis, we mainly focus on providing data analytics for understanding the behavior and interaction of mobile entities (humans and animals). To this end, the main research question to be addressed is: How can behaviors and interactions of mobile entities be determined from mobility data acquired by (mobile) wireless sensor nodes in an accurate and efficient manner? To answer the above-mentioned question, both application requirements and technological constraints are considered in this thesis. On the one hand, applications requirements call for accurate data analytics to uncover hidden information about individual behavior and social interaction of mobile entities, and to deal with the uncertainties in mobility data. Technological constraints, on the other hand, require these data analytics to be efficient in terms of their energy consumption and to have low memory footprint, and processing complexity
All Source Sensor Integration Using an Extended Kalman Filter
The global positioning system (GPS) has become an ubiquitous source for navigation in the modern age, especially since the removal of selective availability at the beginning of this century. The utility of the GPS is unmatched, however GPS is not available in all environments. Heavy reliance on GPS for navigation makes the warfighter increasingly vulnerability as modern warfare continues to evolve. This research provides a method for incorporating measurements from a massive variety of sensors to mitigate GPS dependence. The result is the integration of sensor sets that encompass those examined in recent literature as well as some custom navigation devices. A full-state extended Kalman filter is developed and implemented, accommodating the requirements of the varied sensor sets and scenarios. Some 19 types of sensors are used in multiple quantities including inertial measurement units, single cameras and stereo pairs, 2D and 3D laser scanners, altimeters, 3-axis magnetometers, heading sensors, inclinometers, a stop sign sensor, an odometer, a step sensor, a ranging device, a signal of opportunity sensor, global navigation satellite system sensors, an air data computer, and radio frequency identification devices. Simulation data for all sensors was generated to test filter performance. Additionally, real data was collected and processed from an aircraft, ground vehicles, and a pedestrian. Measurement equations are developed to relate sensor measurements to the navigation states. Each sensor measurement is incorporated into the filter using the Kalman filter measurement update equations. Measurement types are segregated based on whether they observe instantaneous or accumulated state information. Accumulated state measurements are incorporated using delayed-state update equations. All other measurements are incorporated using the numerically robust UD update equations
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Integrating creativity into requirements processes: experiences with an air traffic management system
Requirements engineering is a creative process in which stakeholders and designers work together to create ideas for new systems that are eventually expressed as requirements. This paper describes RESCUE, a scenario driven requirements engineering process that includes workshops that integrate creativity techniques with different types of use case and system context modeling. It reports research in which RESCUE creativity workshops were used to discover stakeholder and system requirements for MSP, a future air traffic management system to enable the more effective, longer term planning of European airspace use. The workshops were successful in that they provided new and important outputs for subsequent requirements processes. The paper describes the workshops structures and results, and answers 3 important research questions
Robustness, Security and Privacy in Location-Based Services for Future IoT : A Survey
Internet of Things (IoT) connects sensing devices to the Internet for the purpose of exchanging information. Location information is one of the most crucial pieces of information required to achieve intelligent and context-aware IoT systems. Recently, positioning and localization functions have been realized in a large amount of IoT systems. However, security and privacy threats related to positioning in IoT have not been sufficiently addressed so far. In this paper, we survey solutions for improving the robustness, security, and privacy of location-based services in IoT systems. First, we provide an in-depth evaluation of the threats and solutions related to both global navigation satellite system (GNSS) and non-GNSS-based solutions. Second, we describe certain cryptographic solutions for security and privacy of positioning and location-based services in IoT. Finally, we discuss the state-of-the-art of policy regulations regarding security of positioning solutions and legal instruments to location data privacy in detail. This survey paper addresses a broad range of security and privacy aspects in IoT-based positioning and localization from both technical and legal points of view and aims to give insight and recommendations for future IoT systems providing more robust, secure, and privacy-preserving location-based services.Peer reviewe
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