Jamming represents the most serious security threat in the field of wireless sensor networks (WSNs), as it can easily put out of order even WSNs that utilize strong highlayer security mechanisms, simply because it is often ignored in the initial WSN design. The objective of this article is to provide a general overview of the critical issue of jamming in WSNs and cover all the relevant work, providing the interested researcher pointers for open research issues in this field. We provide a brief overview of the communication protocols typically used in WSN deployments and highlight the characteristics of contemporary WSNs, that make them susceptible to jamming attacks, along with the various types of jamming which can be exercised against WSNs. Common jamming techniques and an overview of various types of jammers are reviewed and typical countermeasures against jamming are also analyzed. The key ideas of existing security mechanisms against jamming attacks in WSNs are presented and open research issues, with respect to the defense against jamming attacks are highlighted.

A survey on jamming attacks and countermeasures in WSNs

Indoor Human Navigation Systems {a Survey

In this paper, we study estimator inconsistency in vision-aided inertial navigation systems (VINS) from the standpoint of system's observability. We postulate that a leading cause of inconsistency is the gain of spurious information along unobservable directions, which results in smaller uncertainties, larger estimation errors, and divergence. We develop an observability constrained VINS (OC-VINS), which explicitly enforces the unobservable directions of the system, hence preventing spurious information gain and reducing inconsistency. This framework is applicable to several variants of the VINS problem such as visual simultaneous localization and mapping (V-SLAM), as well as visual-inertial odometry using the multi-state constraint Kalman filter (MSC-KF). Our analysis, along with the proposed method to reduce inconsistency, are extensively validated with simulation trials and real-world experimentation.

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Consistency Analysis and Improvement of Vision-aided Inertial Navigation

In this paper, we propose a vision-based location positioning system using augmented reality technique for indoor navigation. The proposed system automatically recognizes a location from image sequences taken of indoor environments, and it realizes augmented reality by seamlessly overlaying the user's view with location information. To recognize a location, we pre-constructed an image database and location model, which consists of locations and paths between locations, of an indoor environment. Location is recognized by using prior knowledge about the layout of the indoor environment. The image sequence is obtained by a wearable mobile PC with camera, which transmits the images to remote PCs for processing. The remote PCs perform marker detection, image sequence matching, and location recognition. The remote PCs transmit the recognized location information to the wearable mobile PC. The system provides the ability to identify similar locations in the image database and display location-related information. Accurate and efficient location positioning is achieved by using several vision-based techniques. The proposed system was tested in an indoor environment and achieved an average location recognition success rate of 89%. The proposed system could be applied to various consumer applications including the door plate system, notice board system, shopping assistance system, and bus service route guide system, among others1.

Vision-based location positioning using augmented reality for indoor navigation

We describe a navigation and location determination system for the blind using an RFID tag grid. Each RFID tag is programmed upon installation with spatial coordinates and information describing the surroundings. This allows for a self-describing, localized information system with no dependency on a centralized database or wireless infrastructure for communications. We describe the system and report on its characteristic performance, limitations, and lessons learned.

RFID information grid for blind navigation and wayfinding

There are many navigation systems for visually impaired people but few can provide dynamic interactions and adaptability to changes. None of these systems work seamlessly both indoors and outdoors. Drishti uses a precise position measurement system, a wireless connection, a wearable computer, and a vocal communication interface to guide blind users and help them travel in familiar and unfamiliar environments independently and safely. Outdoors, it uses DGPS as its location system to keep the user as close as possible to the central line of sidewalks of campus and downtown areas; it provides the user with an optimal route by means of its dynamic routing and rerouting ability. The user can switch the system from an outdoor to an indoor environment with a simple vocal command. An OEM ultrasound positioning system is used to provide precise indoor location measurements. Experiments show an in-door accuracy of 22 cm. The user can get vocal prompts to avoid possible obstacles and step-by-step walking guidance to move about in an indoor environment. This paper describes the Drishti system and focuses on the indoor navigation design and lessons learned in integrating the indoor with the outdoor system.

S. Moore

Papers

Drishti: an integrated indoor/outdoor blind navigation system and service