Surveying human habit modeling and mining techniques in smart spaces

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

On being part of the solution, not the problem: taking a proportionate approach to managing records

Purpose – This article seeks to provide a perspective on a future pathway for records management that is based on taking a proportionate approach rather than striving for perfection. This approach requires a re-interpretation of traditional principles and their application in practice and recognition of the predominance of people in successful information and records management in the digital domain. Design/methodology/approach – The views are the author's based on the headline findings of a major research project (AC+erm) which investigated issues and practical strategies for accelerating positive change in electronic records management. They incorporate views on contextual developments since the project, in particular the characteristics of today's hybrid and increasingly mobile office environment such as the use of recognition technologies. Findings – The ten headline findings of the AC+erm project are shared. Two strategic findings are highlighted, namely, articulating a vision of successful electronic records management and the approach to applying records management principles in order to realise that vision of success. The article then focuses on two of the other findings, about the need for information and records professionals to adopt proportionate and risk based approaches and to ensure they (the records professionals) are an essential part of the solution not the problem. Post the project, views on these and tactics for addressing them are discussed with reference to real examples and potential future research and development. Research limitations/implications – The research that provides the context for the article was qualitative and therefore its findings transferrable rather than generalisable. The views expressed about tactics for moving forward are intended to contribute to the debate about approaches to managing records in the democratic, digital domain. Practical implications – A proportionate approach to managing records by definition implies a risk-based approach. This may prove challenging in organizational, societal and cultural contexts that are risk averse. Originality/value – The research which underpins this article was the first on the subject to be conducted in the UK and adopted a unique evidence-based approach. Undertaken in the context of the “promise” of electronic document and records management systems, its findings are relevant in the broader systems solutions. They provide a context for this perspective on current and potential tactics for addressing strategic issues for managing records in the digital domain. This provides a significant contribution to knowledge and debate in this field

Towards a Comprehensive BPMN Extension for Modeling IoT-Aware Processes in Business Process Models

Internet of Thing (IoT) devices enable the collection and exchange of data over the Internet, whereas Business Process Management (BPM) is concerned with the analysis, discovery, implementation, execution, monitoring, and evolution of business processes. By enriching BPM systems with IoT capabilities, data from the real world can be captured and utilized during process execution in order to improve online process monitoring and data-driven decision making. Furthermore, this integration fosters prescriptive process monitoring, e.g., by enabling IoT-driven process adaptions when deviations between the digital process and the one actually happening in the real world occur. As a prerequisite for exploiting these benefits, IoT-related aspects of business processes need to be modeled. To enable the use of sensors, actuators, and other IoT objects in combination with process models, we introduce a BPMN 2.0 extension with IoT-related artifacts and events. We provide a first evaluation of this extension by applying it in two case studies for modeling of IoT-aware processes

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Complex Event Processing in EPC Sensor Network Middleware for Both RFID and WSN

In an integration system of RFID and wireless sensor network (WSN), RFID is used to identify objects while WSN can provide context environment information of these objects. Thus, it increases system intelligent in pervasive computing. We propose the EPC Sensor Network (ESN) architecture as an integration system of RFID and WSN. This ESN architecture is based on EPCglobal architecture, the de facto international standard for RFID. The core of ESN is the middleware part which is also implemented in our work. In this paper, complex event processing (CEP) technology is used in our ESN middleware which can handle large volume of events from distributed RFID and sensor readers in real time. Through filtering, grouping, aggregating and constructing complex event, ESN middleware provides a more meaningful report for the clients and increases system automation

ASPIE: A Framework for Active Sensing and Processing of Complex Events in the Internet of Manufacturing Things

Rapid perception and processing of critical monitoring events are essential to ensure healthy operation of Internet of Manufacturing Things (IoMT)-based manufacturing processes. In this paper, we proposed a framework (active sensing and processing architecture (ASPIE)) for active sensing and processing of critical events in IoMT-based manufacturing based on the characteristics of IoMT architecture as well as its perception model. A relation model of complex events in manufacturing processes, together with related operators and unified XML-based semantic definitions, are developed to effectively process the complex event big data. A template based processing method for complex events is further introduced to conduct complex event matching using the Apriori frequent item mining algorithm. To evaluate the proposed models and methods, we developed a software platform based on ASPIE for a local chili sauce manufacturing company, which demonstrated the feasibility and effectiveness of the proposed methods for active perception and processing of complex events in IoMT-based manufacturing