It is essential for any highly trained cyclist to optimize his pedalling movement in order to maximize the performance and minimize the risk of injuries. Current techniques rely on bicycle fitting and off-line laboratory measurements. These techniques do not allow the assessment of the kinematics of the cyclist during training and competition, when fatigue may alter the ability of the cyclist to apply forces to the pedals and thus induce maladaptive joint loading. We propose a radically different approach that focuses on determining the actual status of the cyclist’s lower limb segments in real-time and real-life conditions. Our solution is based on body area wireless motion sensor nodes that can collaboratively process the sensory information and provide the cyclists with immediate feedback about their pedalling movement. In this paper, we present a thorough study of the accuracy of our system with respect to the gold standard motion capture system. We measure the knee and ankle angles, which influence the performance as well as the risk of overuse injuries during cycling. The results obtained from a series of experiments with nine subjects show that the motion sensors are within 2.2° to 6.4° from the reference given by the motion capture system, with a correlation coefficient above 0.9. The wireless characteristics of our system, the energy expenditure, possible improvements and usability aspects are further analysed and discussed.

An essential component in the ubiquitous computing vision is the ability of detecting with which objects the user is interacting during his or her activities. We explore in this paper a solution to this problem based on wireless motion and orientation sensors (accelerometer and compass) worn by the user and attached to objects. We evaluate the performance in realistic conditions, characterized by limited hardware resources, measurement noise due to motion artifacts and unreliable wireless communication. We describe the complete solution, from the theoretical design, going through simulation and tuning, to the full implementation and testing on wireless sensor nodes. The implementation on sensor nodes is lightweight, with low communication bandwidth and processing needs. Compared to existing work, our approach achieves better performance (higher detection accuracy and faster response times), while being much more computationally efficient. The potential of the concept is further illustrated by means of an interactive multi-user game. We also provide a thorough discussion of the advantages, limitations and trade-offs of the proposed solution.

A coordinated team of mobile wireless sensor and actuator nodes can bring numerous benefits for various applications in the field of cooperative surveillance, mapping unknown areas, disaster management, automated highway and space exploration. This article explores the idea of mobile nodes using vehicles on wheels, augmented with wireless, sensing, and control capabilities. One of the vehicles acts as aleader, being remotely driven by the user, the others represent thefollowers. Each vehicle has a low-power wireless sensor node attached, featuring a 3D accelerometer and a magnetic compass. Speed and orientation are computed in real time using inertial navigation techniques. The leader periodically transmits these measures to the followers, which implement a lightweight fuzzy logic controller for imitating the leader's movement pattern. We report in detail on all development phases, covering design, simulation, controller tuning, inertial sensor evaluation, calibration, scheduling, fixed-point computation, debugging, benchmarking, field experiments, and lessons learned.

Autonomous vehicles are used in areas hazardous to humans, with significantly greater utility than the equivalent, manned vehicles. This paper explores the idea of a coordinated team of autonomous vehicles, with applications in cooperative surveillance, mapping unknown areas, disaster management or space exploration. Each vehicle is augmented with a wireless sensor node with movement sensing capabilities. One of the vehicles is the leader and is manually controlled by a remote controller. The rest of the vehicles are autonomous followers controlled by wireless actuator nodes. Speed and orientation are computed by the sensor nodes in real time using inertial navigation techniques. The leader periodically transmits these measures to the followers, which implement a lightweight fuzzy logic controller for imitating the leader's movement pattern. The solution is not restricted to vehicles on wheels, but supports any moving entities capable of determining their velocity and heading, thus opening promising perspectives for machine-to-machine and human-to-machine spontaneous interactions in the field. Visit [1] to see a video demonstration of the system.

Context processing in Body Area Networks (BANs) faces unique challenges due to the user and node mobility, the need of real-time adaptation to the dynamic topological and contextual changes, and heterogeneous processing capabilities and energy constraints present on the available devices. This paper proposes a service-oriented framework for the execution of context recognition algorithms. We describe and theoretically analyze the performance of the main framework components, including the sensor network organization, service discovery, service graph construction, service distribution and mapping. The theoretical results are followed by the simulation of the proposed framework as a whole, showing the overall cost of dynamically distributing applications on the network.

We propose a general clustering algorithm for dynamic sensor networks, that makes localized decisions (1-hop neighbourhood) and produces disjoint clusters. The purpose is to extract and emphasise the essential clustering mechanisms common for a set of state-of-the-art algorithms, which allows for a better understanding of these algorithms and facilitates the definition and demonstration of common properties.

Heterogeneous Wireless Sensor Networks (WSNs) are envisioned to provide different types of services in an open and dynamic environment. This paper presents the design, implementation and evaluation of a service discovery and usage solution for heterogeneous WSNs. The users have the possibility to discover and use the services available in the WSN, while sensor nodes can search for the existing gateways to the outside world in order to signal important events. The WSN self-organizes in a clustered structure that acts as a distributed directory of service registrations. The clustering offers the necessary support to achieve energy-efficient discovery within the WSN. We implement the combined solution on resource-constrained sensor nodes, and we analyse the performance characteristics. The results show that the clustering algorithm has low communication overhead and the service discovery protocol scales with the number of nodes and network density. In addition, we show that the solution is lightweight (both code and data memory footprint) and the the interaction user-WSN is straightforward and intuitive.

We propose an energy-efficient service discovery protocol for wireless sensor networks. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimizing the communication costs during discovery of services and maintenance of a functional distributed service registry. We compare theoretically and by simulation the impact of the chosen clustering algorithm on the service discovery protocol