ENRICHING WSN ENVIRONMENT WITH CONTEXT INFORMATION

Currently the Internet of Things environment suffer from a variety of uniqueproblems such as low throughput, inadequate support for mobility and notcompatible(and often close) application environments. However, characteristicof physical environment often provides opportunities to address these problems.This paper explores concepts of enriching the WNS environment withcontext-based information. By context we consider all data available in sensorsenvironment, not only data processed by them. Currently this data are not utilizedby sensors, but we think that they can improve overall functionality of thesensor network. We also discuss the practical challenges facing the integrationof such an approach into the sensor application stack

An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

Ambient Intelligence in Healthcare: A State-of-the-Art

Information technology advancement leads to an innovative paradigm called Ambient Intelligence (AmI). A digital environment is employed along with AmI to enable individuals to be aware to their behaviors, needs, emotions and gestures. Several applications of the AmI systems in healthcare environment attract several researchers. AmI is considered one of the recent technologies that support hospitals, patients, and specialists for personal healthcare with the aid of artificial intelligence techniques and wireless sensor networks. The improvement in the wearable devices, mobile devices, embedded software and wireless technologies open the doors to advanced applications in the AmI paradigm. The WSN and the BAN collect medical data to be used for the progress of the intelligent systems adapted inevitably. The current study outlines the AmI role in healthcare concerning with its relational and technological nature. Health

Modeling of IoT devices in Business Processes: A Systematic Mapping Study

[EN] The Internet of Things (IoT) enables to connect the physical world to digital business processes (BP). By using the IoT, a BP can, e.g.: 1) take into account real-world data to take more informed business decisions, and 2) automate and/or improve BP tasks. To achieve these benefits, the integration of IoT and BPs needs to be successful. The first step to this end is to support the modeling of IoT-enhanced BPs. Although numerous researchers have studied this subject, it is unclear what is the current state of the art in terms of current modeling solutions and gaps. In this work, we carry out a Systematic Mapping Study (SMS) to find out how current solutions are modelling IoT into business processes. After studying 600 papers, we identified and analyzed in depth a total of 36 different solutions. In addition, we report on some important issues that should be addressed in the near future, such as, for instance the lack of standardization.This research has been funded by Internal Funds KU Leuven (Interne Fondsen KU Leuven) and the financial support of the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDF.Torres Bosch, MV.; Serral, E.; Valderas, P.; Pelechano Ferragud, V.; Grefen, P. (2020). Modeling of IoT devices in Business Processes: A Systematic Mapping Study. IEEE. 221-230. https://doi.org/10.1109/CBI49978.2020.00031S22123

Context-based and human-centred information fusion in diagnostics

Maintenance management and engineering practice has progressed to adopt approaches which aim to reach maintenance decisions not by means of pre-specified plans and recommendations but increasingly on the basis of best contextually relevant available information and knowledge, all considered against stated objectives. Different methods for automating event detection, diagnostics and prognostics have been proposed, which may achieve very high performance when appropriately adapted and tuned to serve the needs of well defined tasks. However, the scope of such solutions is often narrow and without a mechanism to include human contributed intervention and knowledge contribution. This paper presents a conceptual framework of integrating automated detection and diagnostics and human contributed knowledge in a single architecture. This is instantiated by an e-maintenance platform comprising tools for both lower level information fusion as well as for handling higher level knowledge. Well structured maintenance relationships, such as those present in a typical FMECA study, as well as on the job human contributed compact knowledge are exploited to this end. A case study presenting the actual workflow of the process in an industrial setting is employed to pilot test the approach

IoT powered servitization of manufacturing – an exploratory case study

More than ever companies are challenged to rethink their offerings while simultaneously being provided with a unique opportunity for creating or recreating their product-service systems. This paper seeks to address how servitisation can utilise the third wave of Internet development, referred to as the Internet of Things (IoT), which may unlock the potential for innovative product-service systems on an unprecedented scale. By providing an analysis of this technological breakthrough and the literature on servitisation, these concepts are combined to address the question of how organisations offering product-service systems can reap the benefits that the IoT. An analysis of three successful IoT implementation cases in manufacturing companies, representing different industry sectors such as metal processing, power generation and distribution, is provided. The results of the empirical research presented in the paper provide an insight into different ways of creating value in servitisation. The paper also proposes a framework that is aimed at proving a better understanding of how companies can create value, and add it to their servitisation processes with, the data obtained by the IoT based solutions. From the value chain perspective, IoT aided servitisation enables organisations to extend their value chains in order better serve their customers which, in turn, might result in increased profitability. The article proposes further research avenues, and offers valuable insight for practitioners.fi=vertaisarvioitu|en=peerReviewed

Ambient Intelligence Systems for Personalized Sport Training

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m; s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.Ministerio de Educación y Ciencia; DEP2006-56158-C03-01/02/03Ministerio de Educación y Ciencia; TEC2007-67966 -01/02/TCM CON-PARTE-1/2Ministerio de Industria, Turismo y Comercio ; TSI-020301-2008-16 ELISAMinisterio de Industria, Turismo y Comercio ; TSI-020301-2008-2 PIRAmID