Vehicle Monitoring System based On IOT, Using 4G/LTE

In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with overcomes the usual delay usually experienced in sending the acquired signals to be processed. The True Vehicle position is represented using google geolocation service and the actual position triangulated in real-time

Control System Development for Small UAV Gimbal

The design process of unmanned ISR systems has typically driven in the direction of increasing system mass to increase stabilization performance and imagery quality. However, through the use of new sensor and processor technology high performance stabilization feedback is being made available for control on new small and low mass stabilized platforms that can be placed on small UAVs. This project develops and implements a LOS stabilization controller design, typically seen on larger gimbals, onto a new small stabilized gimbal, the Tigereye, and demonstrates the application on several small UAV aircraft. The Tigereye gimbal is a new 2lb, 2-axis, gimbal intended to provided high performance closed loop LOS stabilization through the utilization of inertial rate gyro, electronic video stabilization, and host platform state information. Ground and flight tests results of the LOS stabilization controller on the Tigereye gimbal have shown stabilization performance improvements over legacy systems. However, system characteristics identified in testing still limit stabilization performance, these include: host system vibration, gimbal joint friction and backlash, joint actuation compliance, payload CG asymmetry, and gyro noise and drift. The control system design has been highly modularized in anticipation of future algorithm and hardware upgrades to address the remaining issues and extend the system\u27s capabilities

Multimodal, Embodied and Location-Aware Interaction

This work demonstrates the development of mobile, location-aware, eyes-free applications which utilise multiple sensors to provide a continuous, rich and embodied interaction. We bring together ideas from the fields of gesture recognition, continuous multimodal interaction, probability theory and audio interfaces to design and develop location-aware applications and embodied interaction in both a small-scale, egocentric body-based case and a large-scale, exocentric `world-based' case. BodySpace is a gesture-based application, which utilises multiple sensors and pattern recognition enabling the human body to be used as the interface for an application. As an example, we describe the development of a gesture controlled music player, which functions by placing the device at different parts of the body. We describe a new approach to the segmentation and recognition of gestures for this kind of application and show how simulated physical model-based interaction techniques and the use of real world constraints can shape the gestural interaction. GpsTunes is a mobile, multimodal navigation system equipped with inertial control that enables users to actively explore and navigate through an area in an augmented physical space, incorporating and displaying uncertainty resulting from inaccurate sensing and unknown user intention. The system propagates uncertainty appropriately via Monte Carlo sampling and output is displayed both visually and in audio, with audio rendered via granular synthesis. We demonstrate the use of uncertain prediction in the real world and show that appropriate display of the full distribution of potential future user positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user for varying trajectory width and context. We demon- strate the possibility to create a simulated model of user behaviour, which may be used to gain an insight into the user behaviour observed in our field trials. The extension of this application to provide a general mechanism for highly interactive context aware applications via density exploration is also presented. AirMessages is an example application enabling users to take an embodied approach to scanning a local area to find messages left in their virtual environment

Multimodal, Embodied and Location-Aware Interaction

This work demonstrates the development of mobile, location-aware, eyes-free applications which utilise multiple sensors to provide a continuous, rich and embodied interaction. We bring together ideas from the fields of gesture recognition, continuous multimodal interaction, probability theory and audio interfaces to design and develop location-aware applications and embodied interaction in both a small-scale, egocentric body-based case and a large-scale, exocentric `world-based' case. BodySpace is a gesture-based application, which utilises multiple sensors and pattern recognition enabling the human body to be used as the interface for an application. As an example, we describe the development of a gesture controlled music player, which functions by placing the device at different parts of the body. We describe a new approach to the segmentation and recognition of gestures for this kind of application and show how simulated physical model-based interaction techniques and the use of real world constraints can shape the gestural interaction. GpsTunes is a mobile, multimodal navigation system equipped with inertial control that enables users to actively explore and navigate through an area in an augmented physical space, incorporating and displaying uncertainty resulting from inaccurate sensing and unknown user intention. The system propagates uncertainty appropriately via Monte Carlo sampling and output is displayed both visually and in audio, with audio rendered via granular synthesis. We demonstrate the use of uncertain prediction in the real world and show that appropriate display of the full distribution of potential future user positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user for varying trajectory width and context. We demon- strate the possibility to create a simulated model of user behaviour, which may be used to gain an insight into the user behaviour observed in our field trials. The extension of this application to provide a general mechanism for highly interactive context aware applications via density exploration is also presented. AirMessages is an example application enabling users to take an embodied approach to scanning a local area to find messages left in their virtual environment

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Autonomous Vehicle Coordination with Wireless Sensor and Actuator Networks

A coordinated team of mobile wireless sensor and actuator nodes can bring numerous benefits for various applications in the field of cooperative surveillance, mapping unknown areas, disaster management, automated highway and space exploration. This article explores the idea of mobile nodes using vehicles on wheels, augmented with wireless, sensing, and control capabilities. One of the vehicles acts as a leader, being remotely driven by the user, the others represent the followers. Each vehicle has a low-power wireless sensor node attached, featuring a 3D accelerometer and a magnetic compass. Speed and orientation are computed in real time using inertial navigation techniques. The leader periodically transmits these measures to the followers, which implement a lightweight fuzzy logic controller for imitating the leader's movement pattern. We report in detail on all development phases, covering design, simulation, controller tuning, inertial sensor evaluation, calibration, scheduling, fixed-point computation, debugging, benchmarking, field experiments, and lessons learned

Dense and long-term monitoring of Earth surface processes with passive RFID -- a review

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The most mature application today is the study of coarse sediment transport in rivers or coastal environments, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, to monitor the soil moisture or temperature, and to monitor the snowpack temperature and snow water equivalent. RFID sensors, available today, could monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. Key challenges for using RFID monitoring more broadly in geosciences include the use of ground and aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost.Comment: Invited paper for Earth Science Reviews. 50 pages without references. 31 figures. 8 table

A pan-tilt camera Fuzzy vision controller on an unmanned aerial vehicle

is paper presents an implementation of two Fuzzy Logic controllers working in parallel for a pan-tilt camera platform on an UAV. This implementation uses a basic Lucas-Kanade tracker algorithm, which sends information about the error between the center of the object to track and the center of the image, to the Fuzzy controller. This information is enough for the controller, to follow the object moving a two axis servo-platform, besides the UAV vibrations and movements. The two Fuzzy controllers of each axis, work with a rules-base of 49 rules, two inputs and one output with a more significant sector defined to improve the behavior of those

WSN and M2M for mountain biking performance assessment

The thesis describes the design and implementation of the "Smart Mountain Bike” monitoring system enables the acquisition, storage and visualization of data on athlete training referring the cycling activity. The signals provided by the measurement channels are acquired and processed in order to better understand of the variables involved in this sport and consecutively to improve the methodology for the training of athletes. The "Smart Mountain Bike" system consists of a wireless sensor network that acquire data related to the applied force and body position during a training session. Each network end node comprises a microcontroller, a conditioning circuit and a set of sensors. The coordinator node Zig Bee compatible is composed by microcomputer (eg. Raspberry PI or BeagleBone), a GPS and an IMU. The cloud interfacing is done using a 3G/UMTS USB module connected to the microcomputer board. As the main component of the cloud the implemented database is accessed through a mobile application implemented in an Android OS device. The mobile application allows the visualization of the acquired and processed data by the user expressed by the athlete or the coach. This system can be used for other sports and other activities in which it is necessary to monitor physical activities such as physical therapy.Este documento descreve o desenvolvimento de um protótipo "Smart Mountain Bike", este sistema de monitorização permite a recolha, armazenamento e visualização dos dados relativos aos treinos do atleta durante a atividade ciclismo. Esta informação contribui para um melhor entendimento das variáveis envolvidas da prática deste desporto e consecutivamente, melhorar a metodologia de treino dos atletas. O sistema "Smart Mountain Bike" é constituído por uma rede sensores sem fios que recolhe a dados sobre força aplicada e posição do corpo numa sessão de treino, cada nó final da rede é composto por um microcontrolador, um circuito condicionador e um conjunto de sensores. O nó coordenador é composto por um microcomputador, um recetor GPS, um IMU e um módulo de comunicação móvel, este módulo permite um cenário Machine-to-Machine, onde o microcomputador comunica com o a nuvem permitindo o armazenamento da informação recolhida numa base de dados. Esta informação é acedida através de uma aplicação móvel desenvolvida para este projeto, a aplicação móvel permite ao utilizador, atleta ou treinador, visualizar e correlacionar os dados. Este sistema pode ser utilizado noutros desportos e noutras atividades em que seja necessário monitorizar atividades físicas, como por exemplo, fisioterapi