Emanuele Lattanzi

Bio: Emanuele Lattanzi is an academic researcher from University of Urbino. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 16, co-authored 65 publications receiving 830 citations.

Avian soundscapes and cognitive landscapes: theory, application and ecological perspectives

Abstract: The soundscape is proposed as a phenomenological entity with which to investigate environmental complexity. In particular, the avian soundtope, which is defined as a place in which sound is intentionally structured by different bird species, is regarded as an agency acting to achieve several goals. In fact, the soundtope could be viewed as a special case of an eco-field used by birds, not only to establish territorial ownership and patrol an area but also as a means of locating and evaluating the availability of many other material and immaterial resources. The meaning of the multifaceted acoustic pattern produced by bird communities during the breeding season is discussed here under the acoustic niche hypothesis in terms of community coalescence and the permanent establishment of an inter-specific communication network. Furthermore, the spatial and temporal dimensions of a bird soundscape have also been analyzed and discussed in terms of their relationship with environmental proxies. A new Acoustic Complexity Index (ACI), coupled with the implementation (ACI plug-in) of a specific sound editor (WaveSurfer©), is proposed as a way of processing sound data efficiently, thus providing new opportunities to use the bird soundscape signature for landscape characterization and describing the ecological dynamics of long-term monitoring schemes.

SmartRoadSense: Collaborative Road Surface Condition Monitoring

Abstract: —Monitoring of road surface conditions is a criticalactivity in transport infrastructure management. Many researchsolutions have been proposed in order to automatically controland check the quality of road surfaces. Most of them makeuse of expensive sensors embedded in vehicles or mainly focuson detection of specific anomalies during monitoring activity.Inthis paper, we describe the design of a system for collaborativemonitoring of road surface quality. The overall architectureencompasses the integration of a custom mobile application, ageoreferenced database system and a visualization front-end.Road surface condition is summarized through a roughnessparameter computed using signal processing algorithms runningon mobile devices. The roughness values computed are sub-sequently transmitted and stored into a back-end geographicinformation system enabling processing of aggregated tracesand visualization of road conditions. The proposed approachintroduces a thoroughly integrated system suitable for monitoringapplications in a scalable, crowdsourcing collaborative setting.Keywords–Roughness; Accelerometer; Smartphone; Monitor-ing; Cloud.

Spatial and temporal variation of bird dawn chorus and successive acoustic morning activity in a Mediterranean landscape

Abstract: Ecoacoustic techniques using multiple acoustic sensors and two metrics of the acoustic community – the acoustic complexity index (ACI) and the chorus ratio (CR) – were successfully used to describe and characterize the morning acoustic activity of birds according to three equal temporal intervals during spring 2013: Dawn Chorus, Post Chorus 1, and Post Chorus 2.The metrics were applied across five Italian Mediterranean locations (Valenza, Madonna dei Colli, Monte Curto, Virolo, Croce di Tergagliana) that differed by land-cover typologies. Results from the ACI metrics showed a peak during the Dawn Chorus and a visible lull close to sunrise between Dawn Chorus and Post Chorus 1.The lull was evident in all localities except Valenza, where singing activity was relatively constant across the successive morning intervals. Temperature and vegetation structure were confirmed as important factors associated with morning acoustic activities. Vegetation evenness and temperature across the season was negatively corre...

A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case

Abstract: SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed.

Energy Harvesting Sensor Nodes: Survey and Implications

Abstract: Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiting recharge opportunities and tuning performance parameters based on current and expected energy levels, energy harvesting sensor nodes have the potential to address the conflicting design goals of lifetime and performance. This paper surveys various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications. The study also discusses the implications of recharge opportunities on sensor node operation and design of sensor network solutions.

Low Power Wide Area Networks: An Overview

Abstract: Low power wide area (LPWA) networks are attracting a lot of attention primarily because of their ability to offer affordable connectivity to the low-power devices distributed over very large geographical areas. In realizing the vision of the Internet of Things, LPWA technologies complement and sometimes supersede the conventional cellular and short range wireless technologies in performance for various emerging smart city and machine-to-machine applications. This review paper presents the design goals and the techniques, which different LPWA technologies exploit to offer wide-area coverage to low-power devices at the expense of low data rates. We survey several emerging LPWA technologies and the standardization activities carried out by different standards development organizations (e.g., IEEE, IETF, 3GPP, ETSI) as well as the industrial consortia built around individual LPWA technologies (e.g., LoRa Alliance, Weightless-SIG, and Dash7 alliance). We further note that LPWA technologies adopt similar approaches, thus sharing similar limitations and challenges. This paper expands on these research challenges and identifies potential directions to address them. While the proprietary LPWA technologies are already hitting the market with large nationwide roll-outs, this paper encourages an active engagement of the research community in solving problems that will shape the connectivity of tens of billions of devices in the next decade.

Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Abstract: In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systems for wireless industrial communications. We have selected topics that have either emerged as hot topics in the industrial communications community in the last few years (like wireless sensor networks), or which could be worthwhile research topics in the next few years (for example cooperative diversity techniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).

Wireless sensor networks powered by ambient energy harvesting (WSN-HEAP) - Survey and challenges

Abstract: Wireless sensor networks (WSNs) research has pre-dominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial research efforts have been spent on designing energy-efficient networking protocols to maximize the lifetime of WSNs. However, there are emerging WSN applications where sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Examples include in-situ environmental/habitat monitoring and structural health monitoring of critical infrastructures and buildings, where batteries are hard (or impossible) to replace/recharge. Lately, an alternative to powering WSNs is being actively studied, which is to convert the ambient energy from the environment into electricity to power the sensor nodes. While renewable energy technology is not new (e.g., solar and wind) the systems in use are far too large for WSNs. Those small enough for use in wireless sensors are most likely able to provide only enough energy to power sensors sporadically and not continuously. Sensor nodes need to exploit the sporadic availability of energy to quickly sense and transmit the data. This paper surveys related research and discusses the challenges of designing networking protocols for such WSNs powered by ambient energy harvesting.