AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

High-Level Information Fusion in Visual Sensor Networks

Information fusion techniques combine data from multiple sensors, along with additional information and knowledge, to obtain better estimates of the observed scenario than could be achieved by the use of single sensors or information sources alone. According to the JDL fusion process model, high-level information fusion is concerned with the computation of a scene representation in terms of abstract entities such as activities and threats, as well as estimating the relationships among these entities. Recent experiences confirm that context knowledge plays a key role in the new-generation high-level fusion systems, especially in those involving complex scenarios that cause the failure of classical statistical techniques –as it happens in visual sensor networks. In this chapter, we study the architectural and functional issues of applying context information to improve high-level fusion procedures, with a particular focus on visual data applications. The use of formal knowledge representations (e.g. ontologies) is a promising advance in this direction, but there are still some unresolved questions that must be more extensively researched.The UC3M Team gratefully acknowledges that this research activity is supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02

Bio-inspired network security for 5G-enabled IoT applications

Every IPv6-enabled device connected and communicating over the Internet forms the Internet of things (IoT) that is prevalent in society and is used in daily life. This IoT platform will quickly grow to be populated with billions or more objects by making every electrical appliance, car, and even items of furniture smart and connected. The 5th generation (5G) and beyond networks will further boost these IoT systems. The massive utilization of these systems over gigabits per second generates numerous issues. Owing to the huge complexity in large-scale deployment of IoT, data privacy and security are the most prominent challenges, especially for critical applications such as Industry 4.0, e-healthcare, and military. Threat agents persistently strive to find new vulnerabilities and exploit them. Therefore, including promising security measures to support the running systems, not to harm or collapse them, is essential. Nature-inspired algorithms have the capability to provide autonomous and sustainable defense and healing mechanisms. This paper first surveys the 5G network layer security for IoT applications and lists the network layer security vulnerabilities and requirements in wireless sensor networks, IoT, and 5G-enabled IoT. Second, a detailed literature review is conducted with the current network layer security methods and the bio-inspired techniques for IoT applications exchanging data packets over 5G. Finally, the bio-inspired algorithms are analyzed in the context of providing a secure network layer for IoT applications connected over 5G and beyond networks

On Data Management in Pervasive Computing Environments

Abstract—This paper presents a framework to address new data management challenges introduced by data-intensive, pervasive computing environments. These challenges include a spatio-temporal variation of data and data source availability, lack of a global catalog and schema, and no guarantee of reconnection among peers due to the serendipitous nature of the environment. An important aspect of our solution is to treat devices as semiautonomous peers guided in their interactions by profiles and context. The profiles are grounded in a semantically rich language and represent information about users, devices, and data described in terms of “beliefs,” “desires, ” and “intentions. ” We present a prototype implementation of this framework over combined Bluetooth and Ad Hoc 802.11 networks and present experimental and simulation results that validate our approach and measure system performance. Index Terms—Mobile data management, pervasive computing environments, data and knowledge representation, profile-driven caching algorithm, profile driven data management, data-centric routing algorithm. æ