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Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling.

This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases.

This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes.

The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies.

As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques.

Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability.

There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains.

The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers.

As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians.

This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.

Changes in workflow relevant data of business processes at run-time can hinder their completion or impact their profitability as they have been instantiated under different circumstances. The purpose of this paper is to propose a context engine to enhance a business process management (BPM) system’s context-awareness. The generic architecture provides the flexibility to configure processes during initialization as well as to adapt running instances at decision gates or during execution due to significant context change.

The paper discusses context-awareness as the conceptual background. The technological capabilities of business rules and complex event processing (CEP) are outlined in an architecture design. A reference process is proposed and discussed in an exemplary application.

The results provide an improvement over the current situation of static variable instantiation of business processes with local information. The proposed architecture extends the well-known combination of business rules and BPM systems with a context engine based on CEP.

The resulting architecture for a BPM system using a context engine is generic in nature and, hence, requires to be contextualized for situated implementations. Implementation success is dependent on the availability of context information and process compensation options.

Practitioners receive advice on a reference architecture and technology choices for implementing systems, which can provide and monitor context information for business processes as well as intervene and adapt the execution.

Currently, there is no multi-purpose non-proprietary context engine based on CEP or any other technology available for BPM, which facilitates the adaptation of processes at run-time due to changes in context variables. This paper will stimulate a debate between research and practice on suitable design and technology.

The development of context-aware applications in ubiquitous environments depends not only on the user interactions but also on several context parameters. The handling of these parameters is a fundamental problem in these systems. The key purpose of this work is to enrich the unified modeling language (UML) class diagram with new constructs to provide a universal model capable of coping with the context-awareness concerns.

The authors provide a review of existing context handling approaches. Afterward, they relied on the UML extensibility mechanisms to propose a heavyweight extension for the UML class diagram. This generic approach allows describing the different context parameters since the modeling phase.

Existing solutions for context handling apply the contextual constraints on finished applications or tend to be dependent on a specific development process. This paper presents a solution based on UML, which allows dealing with context since the modeling phase, and independently of development processes. This proposal is implemented as an eclipse editor and illustrated through a case study in the healthcare field.

This paper addresses the problem of context handling, and it presents a review of the foremost existing solutions. The paper also presents a heavyweight extension for the UML class diagram, which consists in enriching it with additional constructs, capable of monitoring how applications are linked to context parameters and how the values of these parameters may affect the application behavior.

In many settings, the users are mobile (e.g. away from their desks) while high quality multimedia telephony equipment has fixed locations. This may result in unsuccessful multimedia calls and motivates a context aware system which supports session mobility. This paper aims to address these issues.

The approach is to utilize state‐of‐the‐art in‐context awareness and integrate this into a real time telecom system based on SIP. System requirements are formulated and the system is designed, implemented and (technically) tested.

The paper contains a thorough analysis of why baseline SIP and SIP REFER alone cannot solve our case and why a new SIP extension is introduced. The solution is evaluated and compared to solutions such as “virtual terminals”.

It is pointed out that the context model does not directly support roaming between two different business domains. This issue is however of limited impact in an enterprise setting. The current prototype is thoroughly tested from a technical viewpoint, but user studies in real organizations are recommended as further work.

The paper shows that human issues and issues relating to computer mediated communication (CMC) are strongly linked to technical details in SIP. In practice this means that researchers in CMC and CSCW should look more into building prototypes where real time conversational features are supported together with dynamic change of media types.

The main value of the paper is a thorough described technical realization of the context aware multimedia application ENriched MEdia (ENME). The background material and the appendix should be of value to anyone interested in convergence between computing and communication.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

The ten principles of good business process management (BPM) support organizations in planning and scoping the organizations' BPM approach. Derived from literature and expert panels, the principles received much attention both in research and practice. This article develops a measurement instrument to operationalize the principles and to support organizations in measuring the degree to which they incorporate the principles in their BPM approach, that way advancing their BPM capabilities.

The authors applied the scale-development methodology, because this methodology is an established approach consisting of various techniques to develop measurement instruments. First, the authors used established techniques to develop such an instrument. Then, the authors assessed the validity and reliability of the developed instrument through a field survey with 345 participants.

The authors developed a valid and reliable measurement instrument for the ten principles of good BPM. The field survey's results reveal that the measurement instrument meets all required methodological standards. The instrument, thus, can be applied to help process owners and managers to evaluate their BPM approach and plan future actions based on potential shortcomings. Future research can both use and further develop the instrument, which serves as a conceptualization of the principles.

This study is the first to provide a measurement instrument for assessing an organizations' BPM practice against the ten principles of good BPM, which have become established as a much-considered and widely-used source of reference both in academia and practice. The authors also discuss how the instrument compares to and distinguishes from existing approaches to qualify BPM approaches, thus communicating the significance of the instrument.

This article aims to evaluate a new architecture for scalable decision-making and control in preservation environments for its ability to address five key goals: scalable content profiling; monitoring of compliance, risks and opportunities; efficient creation of trustworthy plans; context awareness; and loosely coupled preservation ecosystems. Scalable decision support and business intelligence capabilities are required to effectively secure content over time.

We conduct a systematic evaluation of the contributions of the SCAPE Planning and Watch suite to provide effective and scalable decision support capabilities. We discuss the quantitative and qualitative evaluation of advancing the state of art and report on a case study with a national library.

The system provides substantial capabilities for semi-automated, scalable decision-making and control of preservation functions in repositories. Well-defined interfaces allow a flexible integration with diverse institutional environments. The free and open nature of the tool suite further encourages global take-up in the repository communities.

The article discusses a number of bottlenecks and factors limiting the real-world scalability of preservation environments. This includes data-intensive processing of large volumes of information, automated quality assurance for preservation actions, and the element of human decision-making. We outline open issues and future work.

The open nature of the software suite enables stewardship organizations to integrate the components with their own preservation environments and to contribute to the ongoing improvement of the systems.

The paper reports on innovative research and development to provide preservation capabilities. The results of the assessment demonstrate how the system advances the control of digital preservation operations from ad hoc decision-making to proactive, continuous preservation management, through a context-aware planning and monitoring cycle integrated with operational systems.