Indoor Geo-location And Tracking Of Mobile Autonomous Robot

The field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking to replacing soldiers for reconnaissance information. Fire fighters use robots for survey of the affected area. Tracking robots has been limited to the local area under consideration. Decision making is inhibited due to limited local knowledge and approximations have to be made. An effective decision making would involve tracking the robot in earth co-ordinates such as latitude and longitude. GPS signal provides us sufficient and reliable data for such decision making. The main drawback of using GPS is that it is unavailable indoors and also there is signal attenuation outdoors. Indoor geolocation forms the basis of tracking robots inside buildings and other places where GPS signals are unavailable. Indoor geolocation has traditionally been the field of wireless networks using techniques such as low frequency RF signals and ultra-wideband antennas. In this thesis we propose a novel method for achieving geolocation and enable tracking. Geolocation and tracking are achieved by a combination of Gyroscope and encoders together referred to as the Inertial Navigation System (INS). Gyroscopes have been widely used in aerospace applications for stabilizing aircrafts. In our case we use gyroscope as means of determining the heading of the robot. Further, commands can be sent to the robot when it is off balance or off-track. Sensors are inherently error prone; hence the process of geolocation is complicated and limited by the imperfect mathematical modeling of input noise. We make use of Kalman Filter for processing erroneous sensor data, as it provides us a robust and stable algorithm. The error characteristics of the sensors are input to the Kalman Filter and filtered data is obtained. We have performed a large set of experiments, both indoors and outdoors to test the reliability of the system. In outdoors we have used the GPS signal to aid the INS measurements. When indoors we utilize the last known position and extrapolate to obtain the GPS co-ordinates

Investigations of 5G localization with positioning reference signals

TDOA is an user-assisted or network-assisted technique, in which the user equipment calculates the time of arrival of precise positioning reference signals conveyed by mobile base stations and provides information about the measured time of arrival estimates in the direction of the position server. Using multilateration grounded on the TDOA measurements of the PRS received from at least three base stations and known location of these base stations, the location server determines the position of the user equipment. Different types of factors are responsible for the positioning accuracy in TDOA method, such as the sample rate, the bandwidth, network deployment, the properties of PRS, signal propagation condition, etc. About 50 meters positioning is good for the 4G/LTE users, whereas 5G requires an accuracy less than a meter for outdoor and indoor users. Noteworthy improvements in positioning accuracy can be achievable with the help of redesigning the PRS in 5G technology. The accuracy for the localization has been studied for different sampling rates along with different algorithms. High accuracy TDOA with 5G positioning reference signal (PRS) for sample rate and bandwidth hasn’t been taken into consideration yet. The key goal of the thesis is to compare and assess the impact of different sampling rates and different bandwidths of PRS on the 5G positioning accuracy. By performing analysis with variable bandwidths of PRS in resource blocks and comparing all the analyses with different bandwidths of PRS in resource blocks, it is undeniable that there is a meaningful decrease in the RMSE and significant growth in the SNR. The higher bandwidth of PRS in resource blocks brings higher SNR while the RMSE of positioning errors also decreases with higher bandwidth. Also, the number of PRS in resource blocks provides lower SNR with higher RMSE values. The analysis with different bandwidths of PRS in resource blocks reveals keeping the RMSE value lower than a meter each time with different statistics is a positivity of the research. The positioning accuracy also analyzed with different sample sizes. With an increased sample size, a decrease in the root mean square error and a crucial increase in the SNR was observed. From this thesis investigation, it is inevitable to accomplish that two different analyses (sample size and bandwidth) done in a different way with the targeted output. A bandwidth of 38.4 MHz and sample size N = 700 required to achieve below 1m accuracy with SNR of 47.04 dB

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Adaptive Geolocation of IoT devices for Active and Assisted Living

Recent developments in IoT devices and communication systems, have brought to light new solutions capable of offering advanced sensing of the surrounding environments. On the other hand, during the last decades, the average life expectancy has increased, which translates into a considerable rise in the number of elderly people. Consequently, in view of all these factors, there is currently a constant demand for solutions to support an Active and Assisted Living (AAL) of such people. The presented thesis intends to propose a solution to help to know the location of IoT devices that may be assisting people. The proposed solution should take into consideration the risk factors of the target group at each moment, as well as the technical constraints of the device, such as its available power energy and means of communications. Thus, ultimately, a profile-based decision should autonomously be made by the device or its integrated system, in order to ensure the usage of the best geolocation technology for each situation.Desenvolvimentos recentes em dispositivos IoT e em sistemas de comunicação, trouxeram consigo novas soluções capazes de oferecer uma deteção avançada dos ambientes circundantes. Por outro lado, no decorrer das últimas décadas, a esperança média de vida aumentou, o que se traduz também num considerável aumento do número de pessoas idosas. Por conseguinte, perante o conjunto destes factores, existe actualmente uma procura constante de soluções de suporte a uma Active and Assisted Living desse grupo de pessoas. A presente tese tenciona propor uma solução que ajude a conhecer a localização dos dispositivos IoT que possam estar a ajudar pessoas. A solução proposta deve ter em consideração os fatores de risco do grupo-alvo em cada momento e também as restrições técnicas do dispositivo, como a energia disponível e os meios de comunicação. Deste modo, em última instância, uma decisão baseada num perfil deve ser tomada autonomamente pelo dispositivo ou pelo seu sistema, para garantir a utilização da tecnologia de geolocalização mais adequada em cada situação

Google earth forensics on IOS 10’s location service

The easy access and common usage of GNSS systems has provided a wealth of evidential information that may be accessed by a digital forensic investigator. Google Earth is commonly used on all manner of devices for geolocation services and consequently has a wide range of tools that will relate real time and stored GNSS data to maps. As an aid to investigation Google Earth forensics is available for use. An investigator can use it by downloading geolocation data from devices and placing it on Google Earth maps, place geolocation data on historical archival maps, or by direct usage of the application in a device. In this paper we review the Google Earth forensics tool and use a simplistic scenario to demonstrate the power of the application for courtroom walk-throughs. The entry-level tool is free and can be used effectively to enhance the presentation of geolocation data

Providing Context to the Clues: Recovery and Reliability of Location Data from Android Devices

Mobile device data continues to increase in significance in both civil and criminal investigations. Location data is often of particular interest. To date, research has established that the devices are location aware, incorporate a variety of resources to obtain location information, and cache the information in various ways. However, a review of the existing research suggests varying degrees of reliability of any such recovered location data. In an effort to clarify the issue, this project offers case studies of multiple Android mobile devices utilized in controlled conditions with known settings and applications in documented locations. The study uses data recovered from test devices to corroborate previously identified accuracy trends noted in research involving live-tracked devices, and it further offers detailed analysis strategies for the recovery of location data from devices themselves. A methodology for reviewing device data for possible artifacts that may allow an examiner to evaluate location data reliability is also presented. This paper also addresses emerging trends in device security and cloud storage, which may have significant implications for future mobile device location data recovery and analysis. Discussion of recovered cloud data introduces a distinct and potentially significant resource for investigators, and the paper addresses the cloud resources\u27 advantages and limitations