Daniele Croce

Overgrid: A Fully Distributed Demand Response Architecture Based on Overlay Networks

In this paper, we present Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed demand response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. As overlay networks in communications establish logical links between peers regardless of the physical topology of the network, the Overgrid is able to apply some power balance criteria to its system of buildings, as they belong to a virtual microgrid, regardless of their physical location. We exploit an innovative distributed algorithm, called flow updating, for monitoring the power consumption of the buildings and the number of nodes in the network, proving its applicability in an Overgrid scenario with realistic power profiles and networks of up to 10 000 buildings. To quantify the energy balance capability of Overgrid, we first study the energy characteristics of several types of buildings in our university campus and in an industrial site to accurately provide some reference buildings models. Then, we classify the amount of “flexible” energy consumption, i.e., the quota that could be potentially exploited for DR programs. Finally, we validate Overgrid emulating a real P2P network of smart buildings behaving according to our reference models. The experimental results prove the feasibility of our approach.

ARIANNA: A smartphone-based navigation system with human in the loop

In this paper we present a low cost navigation system, called ARIANNA, primarily designed for visually impaired people. ARIANNA (pAth Recognition for Indoor Assisted NavigatioN with Augmented perception) permits to find some points of interests in an indoor environment by following a path painted or sticked on the floor. The path is detected by the camera of the smartphone which also generates a vibration signal providing a feedback to the user for correcting his/her direction. Some special landmarks can be deployed along the path for coding additional information detectable by the camera. In order to study the practical feasibility of the ARIANNA system for human users that want to follow a pre-defined path (by only using the smartphone feedback signals), we study how to incorporate human behavior models into the feedback control loop. We also implement an Extended Kalman Filter for localization, in which the user coordinates, speed and orientation represent the filter state (whose updating law depends on the user reaction to the vibration signals), while the smartphones sensors provide the set of measurements used for state estimation.

Learning from errors: Detecting ZigBee interference in WiFi networks

In this work we show how to detect ZigBee interference on commodity WiFi cards by monitoring the reception errors, such as synchronization errors, invalid header formats, too long frames, etc., caused by ZigBee transmissions. Indeed, in presence of non-WiFi modulated signals, the occurrence of these types of errors follows statistics that can be easily recognized. Moreover, the duration of the error bursts depends on the transmission interval of the interference source, while the error spacing depends on the receiver implementation. On the basis of these considerations, we propose the adoption of hidden Markov chains for characterizing the behavior of WiFi receivers in presence of controlled interference sources (training phase) and then run-time recognizing the most likely cause of error patterns. Experimental results prove the effectiveness of our approach for detecting ZigBee interference.

Exploiting programmable architectures for WiFi/ZigBee inter-technology cooperation

The increasing complexity of wireless standards has shown that protocols cannot be designed once for all possible deployments, especially when unpredictable and mutating interference situations are present due to the coexistence of heterogeneous technologies. As such, flexibility and (re)programmability of wireless devices is crucial in the emerging scenarios of technology proliferation and unpredictable interference conditions.In this paper, we focus on the possibility to improve coexistence performance of WiFi and ZigBee networks by exploiting novel programmable architectures of wireless devices able to support run-time modifications of medium access operations. Differently from software-defined radio (SDR) platforms, in which every function is programmed from scratch, our programmable architectures are based on a clear decoupling between elementary commands (hard-coded into the devices) and programmable protocol logic (injected into the devices) according to which the commands execution is scheduled.Our contribution is two-fold: first, we designed and implemented a cross-technology time division multiple access (TDMA) scheme devised to provide a global synchronization signal and allocate alternating channel intervals to WiFi and ZigBee programmable nodes; second, we used the OMF control framework to define an interference detection and adaptation strategy that in principle could work in independent and autonomous networks. Experimental results prove the benefits of the envisioned solution.

Impact of Spreading Factor Imperfect Orthogonality in LoRa Communications

In this paper we study the impact of imperfect-orthogonality in LoRa spreading factors (SFs) in simulation and real-world experiments. First, we analyze LoRa modulation numerically and show that collisions between packets of different SFs can indeed cause packet loss if the interference power received is strong enough. Second, we validate such findings using commercial devices, confirming our numerical results. Third, we modified and extended LoRaSim, an open-source LoRa simulator, to measure the impact of inter-SF collisions and fading (which was not taken into account previously in the simulator). Our results show that non-orthogonality of the SFs can deteriorate significantly the performance especially of higher SFs (10 to 12) and that fading has virtually no impact when multiple gateways are available in space diversity.

Enhancing tracking performance in a smartphone-based navigation system for visually impaired people

In this paper we show how to enhance the tracking performance of Arianna, a low-cost augmented reality system designed to meet the needs of people with problems of orientation, people with sight impairment and blind people. For augmented reality system we mean the design of: i) a set of paths and tags to be deployed in the environment, realized in various ways depending on the context (decorative elements easily identifiable, colorful stripes, QR code, RFID, etc.); ii) an instrument of mediation between the reality and the user (typically a smartphone) to access the information disseminated in the environment by means of a camera and provide a vibration feedback signal to the users for following pre-defined paths. In this paper we explore the possibility of applying optical flow techniques to the sequence of images captured by the camera along the paths, to identify the user movements and provide a position estimate. Experimental results show that the approach is promising.

Demo: unconventional WiFi-ZigBee communications without gateways

Nowadays, the overcrowding of ISM bands is becoming an evident limitation for the performance and widespread usage of 802.11 and 802.15.4 technologies. In this demo, we prove that it is possible to opportunistically exploit the inter-technology interference between 802.11 and 802.15.4 to build an unconventional low-rate communication channel and signalling protocol, devised to improve the performance of each contending technology. Differently from previous solutions, inter-technology communications do not require the deployment of a gateway with two network interfaces, but can be activated (when needed) directly between two heterogeneous nodes, e.g. a WiFi node and a ZigBee node. This capability can be very useful for coordinating channel access between WiFi and ZigBee networks, reading measurements from ZigBee sensors, or configuring ZigBee actuators (e.g. an on/off power switch) directly by using common smartphones or laptops which are only equipped with WiFi interfaces.

ErrorSense: Characterizing WiFi Error Patterns for Detecting ZigBee Interference

Recent years have witnessed the increasing adoption of heterogeneous wireless networks working in unlicensed ISM bands, thus creating serious problems of spectrum overcrowding. Although ZigBee, Bluetooth and WiFi networks have been natively designed for working in presence of interference, it has been observed that several performance impairments may occur because of heterogeneous sensitivity to detect or react to the presence of other technologies. In this paper we focus on the WiFi capability to detect interfering ZigBee links. Despite of the narrowband transmissions performed by ZigBee, in emerging scenarios ZigBee interference can have a significant impact on WiFi performance. Therefore, interference detection is essential for improving coexistence strategies in heterogeneous networks. In our work we show how such a detection can be performed on commodity cards working on time and frequency domain and also analysing data in the error domain. Errors are monitored and classified into error patterns observed in the network in terms of occurrence probability and temporal clustering of different error events. Through statistical analysis we are able to detect the presence of ZigBee transmissions measuring the errors raised by the WiFi card.

Demo: Sensor Fusion Localization and Navigation for Visually Impaired People

We present an innovative smartphone-centric tracking system for indoor and outdoor environments, based on the joint utilization of dead-reckoning and computer vision (CV) techniques. The system is explicitly designed for visually impaired people (although it could be easily generalized to other users) and it is built under the assumption that special reference signals, such as painted lines, colored tapes or tactile pavings are deployed in the environment for guiding visually impaired users along pre-defined paths. Thanks to highly optimized software, we are able to execute the CV and sensor-fusion algorithms in run-time on low power hardware such as a normal smartphone, precisely tracking the users movements.