Section 6 provides details about the proposed monitoringframework; but before doing so, in the following, the paper conducts a quantitative study of the service availability of 5.9 GHz DSRC affected by necessities of the RRP systems, such as the inclusion of RTCM-1004 binary messages into BSMs, as well as DSRC radio parameters and environment in real driving situations. It also explores the service availability of the absolute RTK positioning (RTK w.r.t. a CORS station delivering corrections via NTRIP or other methods) only, as the availability of moving-basedrelative RTK of the RRP systems is the same as the availability of the DSRC sub-system. The integritymonitoringframework will use probability propagation algorithms to determine the availability of the system by considering the individual availability of the V2V communications module, the V2I communications module, the positioning module and the RAIM module. For instance, the availability of the positioning sub-system in every epoch is equal to the sum of the availabilities of modules providing positioning solutions (e.g. RTK positioning module, relative RTK positioning module and built-in sensors) within which the sum of the probabilities of reliable solutions, of false alarms, of solutions with detected errors and of solutions with undetected errors must add to 1. Exploring the service availabilities of both communications and positioning sub-systems requires the knowledge of factors degrading the reliability of each sub-system. The following section provides this required knowledge. Regarding the quantitative study, a series of field experiments under various road and environmental conditions where light traffic was present has been conducted using a fleet of cars equipped with the RRP system as per in . The utilized OBUs and RSUs were developed based on the DSRC protocol stack, including the IEEE 802.11p, IEEE 1609.4, IEEE 1609.3 and SAE-J2735 standards, while using a dual-antenna diversity configuration to quantify 5.9 GHz DSRC link quality of the RRP systems using the Message Delivery Ratio (MDR) factor from the perspective of the application layer.
Figure 1.3. The green curve shows the interpolated (and 30-day predicted) mean TEC based on a least-squares collocation. In addition a 7-parameter trend function - extrapolated for one year - is plotted in yellow. The daily averaged mean TEC values, namely the zero-degree coefficients of the spherical harmonic expansion used to represent the global TEC, are indicated by black dots. As a result, the performance of (absolute and relative) positioning, navigation and timing will experience degradations during these periods of high ionospheric activity. Moreover, the GPS receiver may lose lock on phase and/or amplitude of the signal when local irregularities in electron contents are present in the ionosphere (Chen et al. , 2008). Hence, these phenomena will have direct impact on GPS users in equatorial region since the size and variability of the ionospheric free electron density is usually the largest in this region (Odijk, 2002; Musa, 2007).
GPS is an acronym for Global Positioning System, sometimes called NAVSTAR (NAVstar System with Timing And Ranging), a United States Department of Defence (DoD) satellite-based navigation system. It is a commercially and militarily successful system. GPS can be used for variety of applications in many military and civilian disciplines where highly accurate three dimensional coordinate differences between stations are required. Results can be achieved in a relatively short period and over long lines irrespective of terrain, intervisibility and weather. The system can also be used to determine time, absolute and relative three dimensional positions and velocities in a global coordinate system, all virtually instantaneously. It is cost effective for routine geodetic activities because the instruments are portable and relatively inexpensive to purchase and to operate.
• Temporal perturbation in real-timemonitoringsystems: We build a generic mechanism to apply temporal perturbation to preserve both the tem- poral and measurement privacy in the real-timemonitoringsystems, which is different from the existing temporal perturbation based schemes with high time delay and low utility. Particularly, the logically symmetric Laplace distri- bution is used in the temporal perturbation to keep the uniform distribution of perturbed measurements. With the Laplace noises distribution, the time information in the real-time measurements is differentially private. Besides, perturbed time-series measurements will cause the distortion of individual measurements the system server received, thus protecting measurement pri- vacy with filter-resistance. While, the system server is designed to process and extract crowd statistics from the received measurements via comparing the perturbed time stamps with current time. With the probability characteris- tics of Laplace distribution, the aggregation in a time slot can be estimated in a real-time way from the received measurements, which form a sample space of the large numbers of measurements. Besides real-time aggregation, off-line accumulation can be precisely computed from the temporally perturbed mea- surements on the server side. Therefore, our scheme can also achieve enough data utility in real-timemonitoringsystems.
Time activity data have traditionally been collected by recall telephone interviews or activity logs recorded by study participants [13,14]. However, these methods are limited by accuracy of recall, reliability, and compliance . Recently, new techniques have been used to collect time-location data, such as the use of portable global positioning system (GPS) devices to track people ’ s time- location or commuting patterns with or without corre- sponding participant diary information [15-22]. GPS- based tracking presents an enormous opportunity for improving our understanding of the space-time activities of individuals and how they influence environmental exposure and health outcomes. It offers many advan- tages over traditional methods including near-continu- ous location tracking, high temporal resolution, and minimum reporting burden for participants . How- ever, barriers exist for extracting accurate time activity patterns for human subjects from raw GPS data because they are not consistently reliable due to errors caused by satellite or receiver issues, atmospheric and iono- spheric disturbances, multipath signal reflection, or sig- nal loss or blocking . The multipath problem occurs mainly in urban areas where tall buildings and struc- tures reflect satellite signals many times before they reach a GPS device, leading to GPS coordinate errors .
The main problem of the majority of the positioningsystems is that not always fully three emitters are visible with strong signals and clear line of sight. Thus, manufacturers such as QUALCOMM developed the gpsOne [5, 6] solution for CDMA networks to address the need for accurate commercial-grade, high-availability position location technology. Traditionally, there have been two methods for providing wireless position location information, network-based solutions where the network provides to the mobile its position estimation and handset- based solutions where a mobile node discovers its own position using some precise mechanism. GpsOne merges the two solutions and provides a chipset that triangulate measurement from cellular networks and GPS in order to estimate the user position. Other solutions proposed in  combine the GPS and Dead-Reckoning Navigation Systems to improve accuracy for vehicle positioning or Verizon Wireless  which merges the advantages of both GPS and cellular networks.
A methodology for GPS engineering monitoring using GPS (GPSEM) has been developed and implemented in a software package at the Department of Geomatic Engineering, University College London (UCL). It detects the movements occurring in engineering objects by applying the sidereal-day correction technique for phase GPS multipath errors, a Kalman filter and a Cumulative SUM (CUSUM) control chart. In order to meet the objective of providing a low-cost system, the method uses only L1 phase observables to detect and quantify these movements. After promising success of the system and software on a controlled experiments were conducted to assess previously introduced known movements. The results show that it possible to detect a movement with an accuracy of the order of 1.6 millimeters in real-time with a delay of just three minutes with excellent control over false alarms. The system was implemented in a real engineering project (the Pacoima Dam in California, USA) and it was shown that the method was able to detect deformations that are fully consistent with measured changes in the water surface level in the reservoir. The GPS data processing aspects of the software were verified by comparison of results with a commercial software (SKI-Pro) that uses a different methodology. In summary, an effective, low-cost approach for reliable engineering monitoring using GPS has been developed, and tested in controlled and real engineering environments.
1) Environment Modeling: The continuous construction and updating of background models are indispensable to any video surveillances system. The main prob le m in background modeling is to automatica lly recover and update background fro m a dynamically changing video sequence. Changes in the scene such as moved objects, parked vehicle etc. need to be carefully handled so that interesting foreground targets are detected. In paper , a fra mework is presented for recovering and updating background images based on a process in which a mixed Gaussian model is used for each pixe l value. An online estimat ion is used to upd ate background images in order to adapt to illu mination variance and disturbance in backgrounds. Paper  p roposes a simp le layered modeling technique to update a background model. In addition, important issues related to background updating for visual surveillance are discussed.
In eight stations out of ten considered, positioning with Galileo E1 – E5a IF performs better than GPS L1 – L5 IF, both in terms of accuracy and convergence time. Up to 33% and 29% of improvement, respectively, in the down accuracy level and convergence time can be observed when processing the Galileo E1 – E5a IF compared to GPS L1 – L5 IF. PERT is the only one station where GPS outperforms Galileo in both vertical accuracy and convergence time, while in FFMJ Galileo has worse vertical accuracy but faster convergence time than GPS. The reason why Galileo, in general, performs so much better than GPS has to be addressed to its lower noise that was assumed in the code pseudoranges (Richardson et al., 2016).
These GPS sensors are collocated with tide gauge stations at coast line locations. The system design is similar to the GPS RTR station design using modular components (Sch¨one et al., 2008). GPS data are collected (beside tide gauge data) and locally stored at a rate of 1 Hz. In normal mode the data are sent in configurable time intervals (e.g., some hours) over a BGAN satellite link, sampled down to 1/30 Hz. There is a permanent BGAN receiving link at the station, in order to enable the reception of messages from the warning centre. If the tide gauge station receives a tsunami mode message from the warning centre, or detects a tsunami-like change of the local sea level, it immediately starts to send the most recent 1-Hz data to the warning centre and enters a near real-time data transmission mode to transfer actual measurements. The near real-time data processing system at the warning centre then provides information on possible ground movements. This information can either be used to flag the collocated tide gauge measurements as being not useable (due to a ver- tical sensor station movement) or to correct the tide gauge data measurements with the detected sensor station move- ment values. If not being corrected or flagged invalid a ver- tical tide gauge station movement of a certain value may be misinterpreted as a sea level change of the same value (but in opposite direction).
Due to the tremendous accuracy potential of this system, and the latest improvements in receiver technology, the GPS (Global PositioningSystems) has revolutionized navigation and position location for more than a decade . However GPS signal suffers from inherent imprecision due to a variety of error sources. The combined effects of these errors during signal propagation result in the degradation of positioning accuracy as calculated by the GPS receiver. The commonly held belief is that GPS is accurate to ± X meters, where X is often viewed as acceptable for the purpose of the system under consideration. Fortunately, there are several methods to address these errors and improve the positioning accuracy. For example differential correction technique is often used to combat the satellite and receiver clock errors. Similarly Multipath errors can be reduced to a greater extent by selecting a suitable observation site, using special type of
I would like to express my sincere appreciation to my supervisor, Assoc. Prof. Dr. Tajul Ariffin Musa for his guidance, knowledge, encouragement, critics and motivations in completing this study. Without his continuous supports, this thesis would not have been the same as presented here. I would also like to express my gratitude to all my lecturers in Department of Geoinformation, Faculty Environment Built and Surveying (formerly Faculty of Geoinformation and Real Estate), UTM for every knowledge and moral supports they have given me along my study life in UTM. My sincere appreciation also extended to Postgraduate Staff Puan Norila and Puan Dewi Narty, Geomatic Innovation Research Group (GnG) members Syukriah, Suhaila, Nini, Jehan, Hanifah, Farid, Asyraf, Nazrin, in-laws and others who helped me directly or indirectly in completing this thesis. Your support really means a lot to me.
ABSTRACT: Health monitoringsystems have rapidly evolved recently, and smart systems have been proposed to monitor patient current health conditions, in our proposed and implemented system, we focus on monitoring the patient’s blood glucose level, and his body temperature. Based on last decade statistics of medical records, death rates due to hypertensive heart disease, shows that the blood glucose level is a crucial risk factor for atherosclerosis and ischemic heart diseases; thus, preventive measures should be taken against blood pulse rate which provide the ability to track, trace and save patient’s life at appropriate time is an essential need for mankind. The patient; in any case of emergency a short message service (SMS) will be sent to the Doctor’s mobile number along with the measured values through GSM module. The GPS provides the position information of the monitored person who is under surveillance all the time. This paper demonstrates the feasibility of realizing a complete end-to-end smart health system responding to the real health system design requirements by taking in consideration wider vital human health parameters such as respiration rate, blood glucose level, temperature. The system will be able to bridge the gap between patients - in dramatic health change occasions- and health entities who response and take actions in realtime fashion.
The former storage is handled by OpenTSDB , a software for the storage and configurable plotting of time series. We have chosen OpenTSDB because it is open-source, scalable, and interacts with another open-source distributed database, HBase . It retains time series for a configurable amount of time (defaults to forever), it creates custom graphs on the fly, it allows to plug it into an alerting system such as Nagios . The OpenTSDB’s secret ingredient that helps to increases its reliability, scalability and efficiency is asynchbase. It is a fully asynchronous, non-blocking HBase  client, written from the ground up to be thread-safe for server apps. It has far fewer threads and far less lock contention; it uses less memory and provides more throughput especially for write-heavy workloads. The latter storage, called data sync, receives data destined to further processing, performed by the following subsystem. To enhance the performance of the storage engine, we have chosen to pack the resource data streams in larger chunks (64KB by default) and write them asynchronously to a distributed file system that can be scaled to the appropriate size by easily adding backend nodes. The distributed file system we have chosen is the Hadoop Distributed File System (HDFS). It creates multiple replicas of data blocks and distributes them on compute nodes throughout a cluster to enable reliable, extremely scalable computations. It is also designed to run on commodity hardware, is highly fault-tolerant, provides high throughput access to application data and is suitable for applications that have large data sets.
Data organization in the vehicle positioningmonitoring system is always a difficult and hot issue, and is also a core problem concerning sound and stable system functions . Relevant vehicle positioningmonitoring data mainly includes the following four categories: first, base map data, including administrative divisions, residential areas, gas stations, toll stations, overpasses, residential areas, arterial streets, etc; second, road network data, including road centerline network diagrams, overpasses, scissors crossing and other road network data; third, vehicle monitoring and navigation attribute data, including vehicle location, driving route, distance, direction, speed, length of stay in one position, history data in vehicle operation, etc; at last, business attribute data, including personnel information, vehicle information, driver job information, etc. Fundamental geographic data uses hierarchical management model for design, and can abstract the real world to levels with different characteristics, so as to simplify the system data model and data processing, and improve the flexibility of data organization and management. Road section elements and node elements form a topologically structured road network, which are also the foundation to find the optimal path and to use the road network and vehicle location for map matching . Object-relational database system can better solve object-relational storage of vehicle positioningmonitoring data. According to the characteristics of vehicle operation management and multi- source data analysis, a universal data storage model can be constructed, which is oriented to vehicle positioningmonitoring management services, and meanwhile the Oracle database management system can be used for centralized management and maintenance. Oracle makes an object-oriented expansion in the traditional relational database, and increases the data type of SDO-GEOMETRY dedicated to the storage of geometric entities of geographic objects, which can facilitate the integration of fundamental geographic data, road data, control and navigation attribute data and business data which are all related to vehicle positioningmonitoring for storage management, achieve the storage of the object-relational model, and help data sharing service.
There are some characteristics of our automated GPS- based approach which could limit its use. This method required collecting personal temperature data and uti- lized the strong temperature differences between indoors and outdoors that often occur in Montreal during the winter. This may be feasible in hotter climates where air conditioning is commonly used indoors but could be less useful in climates where milder meteorological con- ditions are found and window opening is typical or in (e.g. fall-spring) seasons where temperature varies less from indoors to outdoors. Kim et al.  recently re- ported a method for assessing time spent indoors using GPS data. The authors were able to identify the number of available satellites being picked up by the GPS and when less than 9 satellites were picked up for a mini- mum of 3 minutes the location was determined as in- doors, this may be a suitable alternative for climates where the temperature differences between indoor and outdoor environments are not as extreme as in Mon- treal. Another study of children’s location assessed the combination of GPS and light sensors, the authors were able to distinguish with moderate to high levels of accur- acy whether the children were indoors or outdoors based on the differences in light intensity in the two lo- cations, there were potential limitations in climates with cloudy conditions . There were also some issues where the GPS signal was missing and data needed to be interpo- lated; while interpolations were limited to only short time periods (where the locations on either side of the gap were the same), some short trips may have been missed.
Weather Data – Remote monitoring can track weather parameters continuously and have pre-set alarm conditions to notify you of action levels. Data from multiple weather stations can be viewed from one location/website. Many weather stations can be powered via solar panels. Well Pad Security – Wireless surveillance with night vision cameras and live web-viewing with continuous monitoring service can prevent and deter vandalism. If needed, the monitoring service can alert 911 to respond. The security systems have significant flexibility including wireless and solar capabilities and are available as fixed or mobile units. They can also be a useful tool for investigating safety incidents using the video footage. Most of our well pad security solutions have involved self-powered 24/7
GPS is weather independent, capable of autonomous operation, and does not require a line-of- sight between target points. GPS is actively and broadly used for positioning in geodetic applica- tions. A typical and highly challenging application – in terms of positioning accuracy –is defor- mation monitoring (Schüler 2007). Recent advances in GPS technology and data processing software have made GPS a much more convenient, accurate and cost-effective tool for deforma- tion monitoring of natural hazards and man-made structures. To date, GPS is widely used to monitor volcano eruptions (Rizos et al. 2000; Roberts and Rizos 2001; Janssen 2002 & 2007), crustal movements (Qiao et al. 2002; Moghtased-Azar and Grafarend 2009), vertical land movements (Teferle et al. 2001), landslides (Brunner et al. 2000; Singer et al. 2009), the open-pit mine (Forward et al. 2001), dams (Hudnut and Behr 1998; Radhakrishnan 2006), buildings (Lovse et al. 1995; Guo and Ge 1997; Chen et al. 2001; Ogaja et al. 2002), and bridges (Roberts et al. 1999; Fujino et al. 2000; Wong et al. 2001; Roberts et al. 2004). A monitoring system for deformation of structures like bridges with real-time capabilities is described by Hein and Riedl (2003). The GPS-basedmonitoring system GOCA (GNSS based online Control and Alarm Sys- tem) developed at the applied university of Karlsruhe can be applied to observe dams, landslides, etc (Jäger et al. 2006). Deformation experiments and GPS deformation monitoring applications have shown that GPS is capable to monitor deformations.