S6: Smart City/Environment 3
- Performance Evaluation of LOADng Routing Protocol in IoT P2P and MP2P Applications
José Victor Vasconcelos Sobral (University of Beira Interior, Portugal); Joel J. P. C. Rodrigues (Instituto de Telecomunicações, University of Beira Interior, Portugal); Kashif Saleem and Jalal Al Muhtadi (King Saud University, Saudi Arabia)
This work presents a performance evaluation study of LOADng routing protocol in Internet of Things (IoT) applications. LOADng is a simplified light version of AODV developed taking into account the limited resources of IoT devices. Initially created in 2011, LOADng emerges as an alternative to the standard RPL protocol. The use of LOADng is justified once several studies has exposed the drawbacks of RPL in applications with multipoint-to-point (MP2P) and point-to-point (P2P) traffic, which are common in IoT environments. With the objective to measure the performance of LOADng in these kinds of traffic, in this work, the LOADng is studied in three network scenarios with divergent size that execute MP2P and P2P applications. The performance evaluation is based on simulation and three network metrics are considered: packet loss rate, spent energy per delivered bit, and end-to-end latency. The obtained results show that, considering the simulated scenarios and the analysed metrics, the LOADng can have a good performance in small networks with MP2P traffic. However, with the growth of the network, the performance is decreased, mainly in P2P applications.
- A Land Similarity Approach to Modeling Complex Ecological Networks
Gianni Fenu and Pier Luigi Pau (University of Cagliari, Italy)
Policies to protect the environment in Europe and in the rest of the world have been adjusted to take into account the network behavior of conglomerates of nature protection areas. Network behavior can emerge from the natural configuration of habitat patches, or be induced by the establishment of habitat corridors. Careful planning is required to protect and improve the network behavior in existing sites; this has prompted researchers to build graph models of ecological networks, and apply complex network analysis to improve the understanding of their features. However, the most common approach is to keep the focus on a single species, meant to be representative of most species within the area under analysis, or especially important with respect to conservation issues. In this paper, data pertaining to land use types found within sites making up the “Natura 2000” ecological network is used to provide a high-level view of the network, and propose a framework for study, in which similarity measures are used as a criterion to suggest guidelines for land management.
- Using Mobile Crowd Sensing for Noise Monitoring in Smart Cities
Marco Zappatore (University of Salento & Alba Project Srl, Italy); Antonella Longo (University of Salento, Italy); Mario Bochicchio (University of Salento Lecce, Italy)
The Smart City model is capturing a constantly growing interest worldwide, boosted by several drivers. On the one hand, novel Information and Communication Technologies (ICTs) disclose promising scenarios to modern cities in terms of innovation, business opportunities and life-quality improvement. On the other hand, increasing requirements on urban resources (e.g., transportation systems, energy consumption and environmental sustainability) pose severe threats to urban infrastructures. One of the possible ways for tackling these challenges is to offer both citizenship and city managers new ways for managing environmental monitoring. Therefore, in this paper we present a Mobile Crowd Sensing (MCS) platform exploiting smartphone’s built-in microphones as sound sensing devices for creating large-scale noise maps and for suggesting city managers suitable noise reduction interventions. Platform architectural and physical components are thoroughly described along with the developed apps. Results from our test site in Southern Italy are presented and discussed, in order to assess how mobile devices can be effectively used as sensing nodes within a Smart City.
- Cleaning up Smart Cities – Localization of Semi-Autonomous Floor Scrubber
Višeslav Čelan, Ivo Stancic and Josip Music (University of Split, Croatia)
The paper describes design and features of novel semi-autonomous floor scrubber add-on module, used for cleaning large indoor and outdoor tile/marbles spaces found in modern (smart) cities. Module is designed in such a manner that it can be easily added to and removed from scrubber machine and that additional sensors and capabilities can be introduced (modular design). In the paper localization capabilities of the machine in three sensor setups are presented and analyzed. Analysis is performed in terms of localization accuracy and reliability as well as associated advantages and disadvantages. Obtained results demonstrated that inclusion of UWB subsystem, despite its price and accuracy (+-20cm in ideal, line of sight, conditions), yields more reliable and accurate results in open spaces (up to 25 times in position and 2 times in orientation) where performance of used Lidar might be sub-optimal.