Real-time auditing of domotic robotic cleaners

Domotic Robotic Cleaners are autonomous devices that are designed to operate almost entirely unattended. In this paper we propose a system that aims to evaluate the performance of such devices by analysis of their trails. This concept of trails is central to our approach, and it encompasses the traditional notion of a path followed by a robot between arbitrary numbers of points in a physical space. We enrich trails with context-specific metadata, such as proximity to landmarks, frequency of visitation, duration, etc. We then process the trail data collected by the robots, we store it an appropriate data structure and derive useful statistical information from the raw data. The usefulness of the derived information is twofold: it can primarily be used to audit the performance of the robotic cleaner –for example, to give an accurate indication of how well a space is covered (cleaned). And secondarily information can be analyzed in real-time to affect the behavior of specific robots – for example to notify a robot that specific areas have not been adequately covered. Towards our first goal, we have developed and evaluated a prototype of our system that uses a particular commercially available robotic cleaner. Our implementation deploys adhoc wireless local networking capability available through a surrogate device mounted onto this commodity robot; the device senses relative proximity to a grid of RFID tags attached to the floor. We report on the performance of this system in experiments conducted in a laboratory environment, which highlight the advantages and limitations of our approach

A formal methodology to design and deploy dependable wireless sensor networks

Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence their effects need to be properly assessed before deployment to obtain a good level of expected performance and during the operation in order to avoid dangerous unexpected results. In this paper we propose amethodology that aims at assessing and improving the dependability level of WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of dependable WSN and a tool ("ADVISES") to simplify its adoption. The tool is applicable to homogeneous WSNs with static routing topologies. It allows to generate automatically formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime for WSNs where an acceptable percentage of faults can be defined. During the runtime we can check the behavior of the WSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, as proof-of-concept, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of the WSN at runtime. Although the method scales up to very large WSNs, the applicability of the methodology maybe compromised by the state space explosion of the reasoning model, which must be faced partitioning large topologies into sub-topologies

Escalation: complex event detection in wireless sensor networks

We present a new approach for the detection of complex events in Wireless Sensor Networks. Complex events are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Our approach is inspired from time-series data mining techniques and transforms a stream of real-valued sensor readings into a symbolic representation. Complex event detection is then performed using distance metrics, allowing us to detect events that are difficult or even impossible to describe using traditional declarative SQL-like languages and thresholds. We have tested our approach with four distinct data sets and the experimental results were encouraging in all cases. We have implemented our approach for the TinyOS and Contiki Operating Systems, for the Sky mote platform

Efficient pattern detection in extremely resource-constrained devices

We present a novel approach for the on-line detection of Complex Events in Wireless Sensor Networks. Complex Events are sets of data points that correspond to unusual patterns that can not be detected using threshold-based techniques. Our method uses an efficient implementation of SAX, a mature data mining algorithm, that transforms a stream of readings into a symbolic representation. Complex Event Detection is then performed via four alternative modes: (a.) multiple pattern detection using a suffix array, (b.) distance-based comparison, (c.) unknown pattern detection, and (d.) probabilistic detection. The method allows users to specify complex events as patterns or to search for interesting changes without supplying any information. The appropriateness of the approach has been verified by applying it to four sensor data sets. In addition, we have developed an efficient implementation for the TinyOS operating system, and further validated our assertions by collecting and analyzing data in real-time

Estimation of pollutant-emitting point-sources using resource-constrained sensor networks

We present an algorithm that makes an appropriate use of a Kalman filter combined with a geometric computation with respect to the localisation of a pollutant-emitting point source. Assuming resource-constrained inexpensive nodes and no specific placement distance to the source, our approach has been shown to perform well in estimating the coordinates and intensity of a source. Using local gossip to directionally propagate estimates, our algorithm initiates a real-time exchange of information that has as an ultimate goal to lead a packet from a node that initially sensed the event to a destination that is as close to the source as possible. The coordinates and intensity measurement of the destination comprise the final estimate. In this paper, we assert that this low-overhead coarse localisation method can rival more sophisticated and computationally-hungry solutions to the source estimation problem

Ubiquitous computing and databases

The concept of the so-called ubiquitous computing was introduced in the early 1990s as the third wave of computing to follow the eras of the mainframe and the personal computer. Unlike previous technology generations, ubiquitous computing recedes into the background of everyday life: It activates the world, makes computers so imbedded, so fitting, so natural, that we use it without even thinking about it, and is invisible, everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere. (Weiser & Brown, 1997, p. 81

Active rules for sensor databases

Recent years have witnessed a rapidly growing interest in query processing in sensor and actuator networks. This is mainly due to the increased awareness of query processing as the most appropriate computational paradigm for a wide range of sensor network applications, such as environmental monitoring. In this paper we propose a second database technology, namely active rules, that provides a natural computational paradigm for sensor network applications which require reactive behavior, such as security management and rapid forest fire response. Like query processing, efficient and effective active rule execution mechanisms have to address several technical challenges including language design, data aggregation, data verification, robustness under topology changes, routing, power management and many more. Nonetheless, active rules change the context and the requirements of these issues and hence a new set of solutions is appropriate. To this end, we outline the implications of active rules for sensor networks and contrast these against query processing. We then proceed to discuss work in progress carried out in project Asene that aims to effectively address these issues. Finally, we introduce our architecture for a decentralized event broker based on the publish/subscribe paradigm and our early design of an ECA language for sensor networks