Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations

We consider Robot-assisted Search $\&$ Rescue operations enhanced with some fixed image sensor nodes capable of capturing and sending visual information to a robot sink. In order to increase the performance of image transfer from image sensor nodes to the robot sinks we propose a 2-hop neighborhood information-based cover set selection to determine the most relevant image sensor nodes to activate. Then, in order to be consistent with our proposed approach, a multi-path extension of Greedy Perimeter Stateless Routing (called T-GPSR) wherein routing decisions are also based on 2-hop neighborhood information is proposed. Simulation results show that our proposal reduces packet losses, enabling fast packet delivery and higher visual quality of received images at the robot sink

Push & Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.Comment: Technical Report. This paper has been published on Wireless Networks, Springer. Animations and the complete code of the proposed algorithm are available for download at the address: http://www.dsi.uniroma1.it/~novella/mobile_sensors

Autonomous Capabilities for Small Unmanned Aerial Systems Conducting Radiological Response: Findings from a High-fidelity Discovery Experiment

This article presents a preliminary work domain theory and identifies autonomous vehicle, navigational, and mission capabilities and challenges for small unmanned aerial systems (SUASs) responding to a radiological disaster. Radiological events are representative of applications that involve flying at low altitudes and close proximities to structures. To more formally understand the guidance and control demands, the environment in which the SUAS has to function, and the expected missions, tasks, and strategies to respond to an incident, a discovery experiment was performed in 2013. The experiment placed a radiological source emitting at 10 times background radiation in the simulated collapse of a multistory hospital. Two SUASs, an AirRobot 100B and a Leptron Avenger, were inserted with subject matter experts into the response, providing high operational fidelity. The SUASs were expected by the responders to fly at altitudes between 0.3 and 30 m, and hover at 1.5 m from urban structures. The proximity to a building introduced a decrease in GPS satellite coverage, challenging existing vehicle autonomy. Five new navigational capabilities were identified: scan, obstacle avoidance, contour following, environment-aware return to home, andreturn to highest reading. Furthermore, the data-to-decision process could be improved with autonomous data digestion and visualization capabilities. This article is expected to contribute to a better understanding of autonomy in a SUAS, serve as a requirement document for advanced autonomy, and illustrate how discovery experimentation serves as a design tool for autonomous vehicles

Horizontal flow fields observed in Hinode G-band images IV. Statistical properties of the dynamical environment around pores

The extensive database of high-resolution G-band images observed with the Hinode/SOT is a unique resource to derive statistical properties of pores using advanced digital image processing techniques. The study is based on two data sets: (1) Photometric and morphological properties inferred from single G-band images cover almost seven years from 2006 October 25 to 2013 August 31. (2) Horizontal flow fields have been derived from 356 one-hour sequences of G-band images using LCT for a shorter period of time from 2006 November 3 to 2008 January 6 comprising 13 active regions. A total of 7643/2863 (single/time-averaged) pores builds the foundation of the statistical analysis. Pores are preferentially observed at low latitudes in the southern hemisphere during the deep minimum of solar cycle No. 23. This imbalance reverses during the rise of cycle No. 24, when the pores migrate from high to low latitudes. Pores are rarely encountered in quiet-Sun G-band images, and only about 10% of pores exists in isolation. In general, pores do not exhibit a circular shape. Typical aspect ratios of the semi-major and -minor axes are 3:2 when ellipses are fitted to pores. Smaller pores (more than two-thirds are smaller than 5~Mm^2) tend to be more circular, and their boundaries are less corrugated. Both area and perimeter length of pores obey log-normal frequency distributions. The frequency distribution of the intensity can be reproduced by two Gaussians representing dark and bright components. Bright features resembling umbral dots and even light-bridges cover about 20% of the pore's area. Averaged radial profiles show a peak of the intensity at normalized radius R_N = r /R_pore = 2.1, followed by maxima of the divergence at R_N= 2.3 and the radial component of the horizontal velocity at R_N= 4.6. The divergence is negative within pores.Comment: 14 pages, 13 figures, Accepted for publication in Astronomy and Astrophysic

Scheduling Sensors for Guaranteed Sparse Coverage

Sensor networks are particularly applicable to the tracking of objects in motion. For such applications, it may not necessary that the whole region be covered by sensors as long as the uncovered region is not too large. This notion has been formalized by Balasubramanian et.al. as the problem of $\kappa$-weak coverage. This model of coverage provides guarantees about the regions in which the objects may move undetected. In this paper, we analyse the theoretical aspects of the problem and provide guarantees about the lifetime achievable. We introduce a number of practical algorithms and analyse their significance. The main contribution is a novel linear programming based algorithm which provides near-optimal lifetime. Through extensive experimentation, we analyse the performance of these algorithms based on several parameters defined

Market analysis of seismic security systems

This report provides information on the commercialization potential of the NASA Activity Monitor. Data on current commercially available products, market size, and growth are combined with information on the NASA technology and the projected impact of this technology on the market

MAP: Medial Axis Based Geometric Routing in Sensor Networks

One of the challenging tasks in the deployment of dense wireless networks (like sensor networks) is in devising a routing scheme for node to node communication. Important consideration includes scalability, routing complexity, the length of the communication paths and the load sharing of the routes. In this paper, we show that a compact and expressive abstraction of network connectivity by the medial axis enables efficient and localized routing. We propose MAP, a Medial Axis based naming and routing Protocol that does not require locations, makes routing decisions locally, and achieves good load balancing. In its preprocessing phase, MAP constructs the medial axis of the sensor field, defined as the set of nodes with at least two closest boundary nodes. The medial axis of the network captures both the complex geometry and non-trivial topology of the sensor field. It can be represented compactly by a graph whose size is comparable with the complexity of the geometric features (e.g., the number of holes). Each node is then given a name related to its position with respect to the medial axis. The routing scheme is derived through local decisions based on the names of the source and destination nodes and guarantees delivery with reasonable and natural routes. We show by both theoretical analysis and simulations that our medial axis based geometric routing scheme is scalable, produces short routes, achieves excellent load balancing, and is very robust to variations in the network model

New Holes and Boundary Detection Algorithm for Heterogeneous Wireless Sensor Networks

Hole is an area in wireless sensor network (WSN) around which nodes cease to sense or communicatedue to drainage of battery or any fault, either temporary or permanent. Holes impair sensing andcommunication functions of network; thus their identication is a major concern. In this paper, adistributed solution is proposed for detecting boundaries and holes in the WSN using only the nodesconnectivity information and estimated distance between nodes. The run of our protocol is dividedinto four main phases. In the rst phase, each node discovers its coverage neighbors and collects theirinformation. In the second phase, each node communicates with its neighbors to nd whether its sensingrange is fully covered by the sensing ranges of its neighbors. In the third phase, the boundary nodesconnect with each other to complete the boundary information. In the fourth phase, a boundary subgraphamongst boundary nodes is constructed and classied either as an interior or an exterior boundary.Simulation results show that our approach improves the energy and reduces the number of boundarynodes over existing algorithms

Coherent, automatic address resolution for vehicular ad hoc networks

Published in: Int. J. of Ad Hoc and Ubiquitous Computing, 2017 Vol.25, No.3, pp.163 - 179. DOI: 10.1504/IJAHUC.2017.10001935The interest in vehicular communications has increased notably. In this paper, the use of the address resolution (AR) procedures is studied for vehicular ad hoc networks (VANETs). We analyse the poor performance of AR transactions in such networks and we present a new proposal called coherent, automatic address resolution (CAAR). Our approach inhibits the use of AR transactions and instead increases the usefulness of routing signalling to automatically match the IP and MAC addresses. Through extensive simulations in realistic VANET scenarios using the Estinet simulator, we compare our proposal CAAR to classical AR and to another of our proposals that enhances AR for mobile wireless networks, called AR+. In addition, we present a performance evaluation of the behaviour of CAAR, AR and AR+ with unicast traffic of a reporting service for VANETs. Results show that CAAR outperforms the other two solutions in terms of packet losses and furthermore, it does not introduce additional overhead.Postprint (published version