Pedro Castillejo

Integration of wearable devices in a wireless sensor network for an E-health application

Applications based on Wireless Sensor Networks for Internet of Things scenarios are on the rise. The multiple possibilities they offer have spread towards previously hard to imagine fields, like e-health or human physiological monitoring. An application has been developed for its usage in scenarios where data collection is applied to smart spaces, aiming at its usage in fire fighting and sports. This application has been tested in a gymnasium with real, non-simulated nodes and devices. A Graphic User Interface has been implemented to suggest a series of exercises to improve a sportsman/woman s condition, depending on the context and their profile. This system can be adapted to a wide variety of e-health applications with minimum changes, and the user will interact using different devices, like smart phones, smart watches and/or tablets.

An Internet of Things Approach for Managing Smart Services Provided by Wearable Devices

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices is the wearable devices, and the wireless sensor networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper, we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario, where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an enterprise service bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, and computers) and operating systems (Android, iOS, Windows, Linux, etc.).

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

SMArc: A Proposal for a Smart, Semantic Middleware Architecture Focused on Smart City Energy Management

Among the main features that are intended to become part of what can be expected from the Smart City, one of them should be an improved energy management system, in order to benefit from a healthier relation with the environment, minimize energy expenses, and offer dynamic market opportunities. A Smart Grid seems like a very suitable infrastructure for this objective, as it guarantees a two-way information flow that will provide the means for energy management enhancement. However, to obtain all the required information, another entity must care about all the devices required to gather the data. What is more, this entity must consider the lifespan of the devices within the Smart Grid—when they are turned on and off or when new appliances are added—along with the services that devices are able to provide. This paper puts forward SMArc—an acronym for semantic middleware architecture—as a middleware proposal for the Smart Grid, so as to process the collected data and use it to insulate applications from the complexity of the metering facilities and guarantee that any change that may happen at these lower levels will be updated for future actions in the system.

A Semantic-Middleware-Supported Receding Horizon Optimal Power Flow in Energy Grids

Energy management in electric grids with multiple energy sources, generators, storage devices, and interacting loads along with their complex behaviors requires grid wide control. Communication infrastructure that aggregates information from heterogeneous devices in the electric grid making the applications completely independent of physical connectivity is essential for building in the context of control applications. This investigation presents a semantic middleware that is used to implement a receding-horizon-based optimal power flow (OPF) in smart grids. The presence of renewable energy sources, storage systems, and loads dispersed all along the grid necessitates the use of grid wide control and a communication infrastructure to support it. To this extent, the proposed middleware will serve as the basis for representing various components of the power grid. It is enriched with intelligence by semantic annotation and ontologies that provide situation awareness and context discovery. The middleware deployment is demonstrated by implementing the receding horizon OPF in a network in Steinkjer, Norway. Our results demonstrate the advantages of both the middleware and the algorithm. Furthermore, the results prove the added flexibility obtained in the grid due to the addition of renewable energy and storage systems. The significant advantage of the proposed approach is that the real-time monitoring infrastructure is used for improving the flexibility, reliability, and efficiency of the grid.

Fuzzy-Based adaptive countering method against false endorsement insertion attacks in wireless sensor networks

Wireless sensor networks (WSNs) are vulnerable to false endorsement insertion attacks (FEIAs), where a malicious adversary intentionally inserts incorrect endorsements into legitimate sensing reports in order to block notifications of real events. A centralized solution can detect and adaptively counter FEIAs while conserving the energy of the forwarding nodes because it does not make the nodes verify reports using cryptographic operations. However, to apply this solution to a WSN, the users must carefully select 10 or more security parameters, which are used to determine the occurrences of FEIAs. Thus, an inappropriate choice of a single parameter might result in the misinterpretation of or misdetection of FEIAs. Therefore, the present study proposes a fuzzy-based centralized method for detecting and adaptively countering FEIAs in dense WSNs, where two fuzzy rule-based systems are used to detect an FEIA and to select the most effective counter measure against the FEIA. A major benefit of the proposed method is that the fuzzy systems can be optimized automatically by combining a genetic algorithm and a simulation. Thus, users only need to write a model of the WSN to apply the proposed method to a WSN. The improved performance with this method is demonstrated by simulation results.Wireless sensor networks (WSNs) based on wearable devices are being used in a growing variety of applications, many of them with strict privacy requirements: medical, surveillance, e-Health, and so forth. Since private data is being shared (physiological measures, medical records, etc.), implementing security mechanisms in these networks has become a major challenge. The objective of deploying a trustworthy domain is achieving a nonspecific security mechanism that can be used in a plethora of network topologies and with heterogeneous application requirements. Another very important challenge is resilience. In fact, if a stand-alone and self-configuring WSN is required, an autosetup mechanism is necessary in order to maintain an acceptable level of service in the face of security issues or faulty hardware. This paper presents SensoTrust, a novel security model for WSN based on the definition of trustworthy domains, which is adaptable to a wide range of applications and scenarios where services are published as a way to distribute the acquired data. Security domains can be deployed as an add-on service to merge with any service already deployed, obtaining a new secured service.

Automated determination of security services to ensure personal data protection in the Internet of Things applications

This paper describes a method aimed at automatically determining security services to be implemented in products, services and devices involved on the Internet of Things scenarios. It is important to consider the specific context, legislative diversity and nature of the information since its main objective is to have correct and fair data processing that avoids users in perceiving any danger to their privacy. This paper gives a brief overview based on several types of security threat scenarios. It tries to introduce “Utility Matrix” concept that connects involved users, their security needs, and legal imperatives all together. Based on “Utility Matrix”, an expert system is proposed in order to automate security service decisions and solution for personal data protection on the area of Internet of Things. Different approaches are presented, and several applied use cases are given for AWARE product, such as application. This automated system is in the development phase. Nevertheless, this project has to connect areas of the Industry to the judicial and technology, taking into account that users are in the middle of the scenario. As a result of this project, a certificate of personal data protection to users and companies could be obtained. It could be a tool to simulate and evaluate the impact of new services, new laws, and new needs in technology and research.

A Privacy Protection User Authentication and Key Agreement Scheme Tailored for the Internet of Things Environment: PriAuth

In a wearable sensor-based deployment, sensors are placed over the patient to monitor their body health parameters. Continuous physiological information monitored by wearable sensors helps doctors have a better diagnostic and a suitable treatment. When doctors want to access the patient’s sensor data remotely via network, the patient will authenticate the identity of the doctor first, and then they will negotiate a key for further communication. Many lightweight schemes have been proposed to enable a mutual authentication and key establishment between the two parties with the help of a gateway node, but most of these schemes cannot enable identity confidentiality. Besides, the shared key is also known by the gateway, which means the patient’s sensor data could be leaked to the gateway. In PriAuth, identities are encrypted to guarantee confidentiality. Additionally, Elliptic Curve Diffie–Hellman (ECDH) key exchange protocol has been adopted to ensure the secrecy of the key, avoiding the gateway access to it. Besides, only hash and XOR computations are adopted because of the computability and power constraints of the wearable sensors. The proposed scheme has been validated by BAN logic and AVISPA, and the results show the scheme has been proven as secure.

Wireless sensor networks in knowledge management

Abstract Research in Wireless Sensor Networks (WSN) necessarily touches on many research topics of Computer Science, Electronic Engineering and Telecommunication, basing on the existing work in related fields. However, the peculiarity of the WSN field is the interplay and integration of these foundation subjects, yielding a distinct topic worthy of further study in its own right. One of the main open issues in WSN research is to abstract the applications of complex low-level mechanisms, and one of the most powerful and flexible ways to achieve this is creating a Middleware layer that cover all this functionality, provide services to applications, allows the intercommunication among components, adapts dynamically to different operation modes and clearly differentiated from low-level components. Knowledge management and ontologies are also helpful when WSN are used to monitoring and taking decisions. We deploy a WSN in a testing scenario in order to control environmental parameters according to user profile stored in the system.

A Novel Context Ontology to Facilitate Interoperation of Semantic Services in Environments with Wearable Devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a non-intrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project.