Wi-Fi For Indoor Device Free Passive Localization (DfPL): An Overview

The world is moving towards an interconnected and intercommunicable network of animate and inanimate objects with the emergence of Internet of Things (IoT) concept which is expected to have 50 billion connected devices by 2020. The wireless communication enabled devices play a major role in the realization of IoT. In Malaysia, home and business Internet Service Providers (ISP) bundle Wi-Fi modems working in 2.4 GHz Industrial, Scientific and Medical (ISM) radio band with their internet services. This makes Wi-Fi the most eligible protocol to serve as a local as well as internet data link for the IoT devices. Besides serving as a data link, human entity presence and location information in a multipath rich indoor environment can be harvested by monitoring and processing the changes in the Wi-Fi Radio Frequency (RF) signals. This paper comprehensively discusses the initiation and evolution of Wi-Fi based Indoor Device free Passive Localization (DfPL) since the concept was first introduced by Youssef et al. in 2007. Alongside the overview, future directions of DfPL in line with ongoing evolution of Wi-Fi based IoT devices are briefly discussed in this paper

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Workshop on "Control issues in the micro / nano - world".

International audienceDuring the last decade, the need of systems with micro/nanometers accuracy and fast dynamics has been growing rapidly. Such systems occur in applications including 1) micromanipulation of biological cells, 2) micrassembly of MEMS/MOEMS, 3) micro/nanosensors for environmental monitoring, 4) nanometer resolution imaging and metrology (AFM and SEM). The scale and requirement of such systems present a number of challenges to the control system design that will be addressed in this workshop. Working in the micro/nano-world involves displacements from nanometers to tens of microns. Because of this precision requirement, environmental conditions such as temperature, humidity, vibration, could generate noise and disturbance that are in the same range as the displacements of interest. The so-called smart materials, e.g., piezoceramics, magnetostrictive, shape memory, electroactive polymer, have been used for actuation or sensing in the micro/nano-world. They allow high resolution positioning as compared to hinges based systems. However, these materials exhibit hysteresis nonlinearity, and in the case of piezoelectric materials, drifts (called creep) in response to constant inputs In the case of oscillating micro/nano-structures (cantilever, tube), these nonlinearities and vibrations strongly decrease their performances. Many MEMS and NEMS applications involve gripping, feeding, or sorting, operations, where sensor feedback is necessary for their execution. Sensors that are readily available, e.g., interferometer, triangulation laser, and machine vision, are bulky and expensive. Sensors that are compact in size and convenient for packaging, e.g., strain gage, piezoceramic charge sensor, etc., have limited performance or robustness. To account for these difficulties, new control oriented techniques are emerging, such as[d the combination of two or more ‘packageable' sensors , the use of feedforward control technique which does not require sensors, and the use of robust controllers which account the sensor characteristics. The aim of this workshop is to provide a forum for specialists to present and overview the different approaches of control system design for the micro/nano-world and to initiate collaborations and joint projects

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Master of Science

thesisDevice-free localization (DFL) systems are used to locate a person in an environment by measuring the changes in received signal strength (RSS) on all the links in the network. A fingerprint-based DFL method, such as the type addressed in this thesis, collects a database of RSS fingerprints and uses a machine learning classifier to determine a person's location. However, as the environment changes over time due to furniture or other objects being moved, the RSS fingerprints diverge further and further from those stored in the database, causing the accuracy of the system to suffer. This thesis investigates the degradation over time of localization accuracy in radio frequency (RF) sensor networks using a fingerprint-based method with a machine learning classifier. We perform extensive experiments that allow quantification of how changes in an environment affect accuracy, through a process of moving specific items in a residential home one at a time and conducting separate localization experiments after each change. We find that the random forests classifier performs the best as changes are made, compared to three other classifiers tested. In addition, we present a correlation method for selecting the channel used with each link, which improves localization accuracy from an average of 95.2% to an overall 98.4% accuracy using random forests. We thus demonstrate that combining the random forests classifier with a correlation method of selecting a channel for each link offers a viable approach to developing a more robust system for device-free localization that is less susceptible to changes in the environment

From Real to Complex: Enhancing Radio-based Activity Recognition Using Complex-Valued CSI

Activity recognition is an important component of many pervasive computing applications. Radio-based activity recognition has the advantage that it does not have the privacy concern and the subjects do not have to carry a device on them. Recently, it has been shown channel state information (CSI) can be used for activity recognition in a device-free setting. With the proliferation of wireless devices, it is important to understand how radio frequency interference (RFI) can impact on pervasive computing applications. In this paper, we investigate the impact of RFI on device-free CSI-based location-oriented activity recognition. We present data to show that RFI can have a significant impact on the CSI vectors. In the absence of RFI, different activities give rise to different CSI vectors that can be differentiated visually. However, in the presence of RFI, the CSI vectors become much noisier and activity recognition also becomes harder. Our extensive experiments show that the performance of state-of-the-art classification methods may degrade significantly with RFI. We then propose a number of counter measures to mitigate the impact of RFI and improve the location-oriented activity recognition performance. We are also the first to use complex-valued CSI to improve the performance in the environment with RFI