Accurate, simple and affordable methods for passive indoor tracking of human beings are still missing. In this article, we describe the development of an unobtrusive two-dimensional human positioning system based on low-frequency electric fields. The system's operation is based on measuring the capacitance between multiple floor tiles and a receiving electrode. The presented system is invisible to the user and uses a single-chip solution to measure the capacitances. The implemented system is evaluated with two different types of receiving electrodes and the results are presented. With the used tiles, the system can locate a standing human with at least 15 cm accuracy and track a walking person with at least 41 cm accuracy. The update rate of the system is 10 Hz.
Proactive, context-aware computing isn't new. In 2000, David Tennenhouse called for a change in the boundary between the physical and virtual worlds. He identified proactive computing as an alternative to interactive computing and defined how future systems should become more involved with the real world. He also considered context-aware control systems with online adaptation especially promising. Today, ambient-intelligence researchers show increasing interest in both proactive applications and context-aware applications. Using different context-recognition methods, researchers can easily gather application-specific information from the environment and enable context-triggered actions. According to Hee Eon Byun and Keith Cheverst, a context-aware home can serve its inhabitants more flexibly and adaptively than an ordinary home. They also claim that proactive systems can be built using machine-learning algorithms with context recognition. In addition to context recognition, adaptivity is essential in intelligent environments. In terms of computing systems, the environment can adjust itself using adaptation mechanisms to comply with user preferences; it can become unobtrusive and better support user activities. A home adapting to its inhabitants' living style is much more convenient than a user adapting to the home's behavior. In this article, we show how to develop a proactive, adaptive, fuzzy home-control system, present the algorithm we used for adaptation, and evaluate the test results we obtained.
Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic literature, but information management-focused twins that combine multiple systems are scarce. This study presents, analyzes, and draws recommendations from building a multi-component digital twin as an industry-university collaboration project and related smaller works. The objective of the studied project was to create a prototype implementation of an industrial digital twin for an overhead crane called “Ilmatar”, serving machine designers and maintainers in their daily tasks. Additionally, related cases focus on enhancing operation. This paper describes two tools, three frameworks, and eight proof-of-concept prototypes related to digital twin development. The experiences show that good-quality Application Programming Interfaces (APIs) are significant enablers for the development of digital twins. Hence, we recommend that traditional industrial companies start building their API portfolios. The experiences in digital twin application development led to the discovery of a novel API-based business network framework that helps organize digital twin data supply chains.
1 January 2012 in Journal of Ambient Intelligence and Smart Environments
In smart homes, unobtrusive monitoring of user position and activity are important but challenging tasks. With the current state of technology, this task is especially hard to carry out in private areas where video surveillance is considered undesira
1 January 2011 in Journal of Ambient Intelligence and Smart Environments
In pervasive context recognition and user identification applications, unobtrusive recognition of user height and posture is difficult. With the current state of technology, this becomes even harder in environments where cameras are not desired or al