Accurate, inexpensive, and reliable real-time indoor localization holds the key to the full potential of the context-aware applications and location-based Internet of Things (IoT) services. State-of-the-art indoor localization systems are coping with the complex non-line-of-sight (NLOS) signal propagation which hinders the use of proven multiangulation and multilateration methods, as well as with prohibitive installation costs, computational demands, and energy requirements. In this paper, we present a novel sensor utilizing low-range infrared (IR) signal in the line-of-sight (LOS) context providing high precision angle-of-arrival (AoA) estimation. The proposed sensor is used in the pragmatic solution to the localization problem that avoids NLOS propagation issues by exploiting the powerful concept of the wireless sensor network (WSN). To demonstrate the proposed solution, we applied it in the challenging context of the supermarket cart navigation. In this specific use case, a proof-of-concept navigation system was implemented with the following components: IR-AoA sensor prototype and the corresponding WSN used for cart localization, server-side application programming interface (API), and client application suite consisting of smartphone and smartwatch applications. The localization performance of the proposed solution was assessed in, altogether, four evaluation procedures, including both empirical and simulation settings. The evaluation outcomes are ranging from centimeter-level accuracy achieved in static-1D context up to 1 m mean localization error obtained for a mobile cart moving at 140 cm/s in a 2D setup. These results show that, for the supermarket context, appropriate localization accuracy can be achieved, along with the real-time navigation support, using readily available IR technology with inexpensive hardware components.

In recent years we have witnessed strong development and widespread use of powerful wirelessly connected platforms, thus the set of the related problems that need to be solved by distributed algorithms is growing rapidly. Some of them present large obstacles in harnessing the full potential of this new technology, so there is an imminent need for a fast and easy evaluation of new ideas and approaches. Simulation is a fundamental part of distributed algorithm design and evaluation process. In this paper, we present a library for event-based simulation and evaluation of distributed algorithms. This library provides a set of simple but powerful tools with a goal to ease virtual setup of a complex system such as a distributed network of communicating entities and to define, simulate, and analyze its behavior. In order to reduce a huge problem space inherent in such systems, our library is using a high level of abstraction. This is made possible by a strict and complete definition of the distributed computing environment. The library is implemented in Python whose simple and expressive syntax provides a possibility of minimal implementations and a mild learning curve. In addition to executing automated simulations or larger experiments, the library fully supports interactive mode along with a step-by-step execution, which can be a very powerful combination.

A localization problem in wireless sensor and ad hoc networks can be solved using measured distances and/or directions between neighboring nodes as constraints. With the internode constraints only the relative localization problem can be solved, as for more specific absolute positions a set of prelocalized nodes, called anchors, is needed. In this paper, a new approach for designing and evaluating a distributed anchor-free localization algorithm is presented. It uses only direction constraints relative to the nodepsilas coordinate system as their orientations are assumed to be unknown. The algorithm is based on division of a network into clusters. After the initial clusters are localized, by stitching them together the whole network can be localized. Using the graph rigidity theory we define new structures and their relationships, so the algorithm can provide relative locations to maximum number of nodes for a given number of constraints. The algorithm performance is evaluated through simulations and the obtained results are similar to the centralized version of algorithm. Additional analysis showed that the performance is not dependant on the path and order used for cluster stitching. By comparing the performance to the Cramer Rao bound it is revealed that the error induced by the algorithm correspond to the 30% - 50% of the total localization error.

In the area of Human-Computer Interaction (HCI), the concept of Around Device Interaction (ADI) is gaining special attention nowadays. It provides the possibility of interacting with the device by making use of gestures made in the surrounding space, as well as by detecting certain ambient changes, thus eliminating the need of direct physical contact. Contact-free interaction can be useful for wearable and smart devices, especially in cases where operating with small buttons and touchscreens appears to be particularly inconvenient. This paper presents alternative techniques for smartphone interaction based on different sensory inputs. Namely, external sources of magnetic field, light, and infrared (IR) signals are used to manipulate device sensors' readings which are in turn interpreted as the corresponding interaction commands. Proof-of-concept mobile applications are developed and here presented, demonstrating both the potentials and utility of the contact-free interaction. Specifically, small neodymium magnet was used for smartphone text entry, typical battery flashlight served for sending information to device via Morse code, as well as for alarm triggering, and voice-enabled control device was utilized for invoking smartphone calls from a distance. The presented interaction techniques do not require smartphone hardware alterations. While the usage of built-in magnetic field and ambient light sensors is assumed, peripheral infrared receiver can be used in order to provide IR-based support.