Smart object

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A smart object ( English smart object ) is an object that by embedding information technology has capabilities that go beyond its original purpose. The advanced capabilities of such objects are to acquire, process and store data and to interact with their environment.

Basics

motivation

The idea underlying the creation of intelligent objects is to close the gap between the real world, which can be physically experienced, and the digital world, which is present in information systems . Intelligent objects form the basis for the vision of ubiquitous computing . In this vision, which was largely developed at the Xerox PARC , the boundary between computers and everyday objects disappears, in which information technologies merge with everyday objects and can be used anywhere. The aim is to support people with intuitive, usable devices. The concept of the Internet of Things is to be understood in a similar way , in which intelligent everyday objects that have digital logic, sensors and communication capabilities come together in networks. From a business perspective, these intelligent objects are particularly interesting for digitally capturing additional information about the status of objects and processes. So-called high resolution management aims to support management tasks such as planning, leadership and controlling through automated data acquisition. The information technologies used are used to obtain information at shorter time intervals, with a higher level of detail (ideally at the level of an individual article) and with additional status information (e.g. the current temperature). The fact that data acquisition results in lower costs due to automation means that the number of measurements can be increased and the company's planning can be adapted more frequently to the real conditions.

Skills

The definition of smart objects as objects that receive an extended range of functions through information technology covers a large number of different applications. For the general description of smart objects, the essential functions can be divided into five categories:

Applications

Private applications of smart objects

The previously introduced technological structure of the capabilities is possible both for applications of smart objects in the company and for applications that increase the product functionality for a private user. After the definition of intelligent objects that was made at the beginning, an extremely broad framework is spanned in the area of ​​private applications, in which further categorization is hardly possible.

Operational applications of smart objects

A more extensive categorization of the functions is possible in the operational context. A distinction can be made between three areas, each of which requires a different scope of embedded technologies. A fundamental function that can be implemented with smart objects is the real-time acquisition of data within the operational processes. With the help of intelligent objects, information about the location, condition and surroundings of objects can be made available promptly. The second essential function arises when the capabilities of the objects are expanded in such a way that decentralized information processing and decision-making are also possible. In this case, the decision to start or end a process can be transferred directly to suitable objects. An even more extensive transfer of tasks to the objects takes place when objects can carry out complete business processes individually or by being networked with one another, for example a logistical object finds its way independently through a logistic environment.

Applications can already be found in the field of logistics and healthcare . To optimize supply chains, intelligent objects can be used that can automatically identify themselves at the outgoing goods of a supplier and in the incoming goods of a customer (e.g. through RFID ). In this way, the current stocks along the supply chain can be recorded at any time with little effort and without manual data entry. In connection with an inter-company data exchange, the dreaded whip effect can be combated. The intelligent objects can serve as a technological basis for improved planning approaches ( e.g. collaborative planning, forecasting and replenishment ).

In the healthcare sector, applications can already be found that, in addition to pure identification, also use other functions of smart objects. One example is the support of a blood transfusion through wireless sensor networks . Several different functions can be performed with the help of embedded information technologies. By integrating a sensor node with a temperature probe in a transfusion bag, the temperature on the surface of the blood product can be continuously monitored. These values ​​are transferred to an evaluation system in the background, and if threshold values ​​are violated, the responsible staff can be informed of the possible quality defects. If the patients are also equipped with a wristband with sensor nodes, an automatic comparison between the information from the patient and the blood product can be carried out. Built-in LEDs, which act as actuators here, can warn the staff about a transfusion if the patient and the blood product are incompatible.

Technologies

The basic function for many applications of smart objects is the clear identification of objects. This is particularly true for logistical applications in which the localization of objects by recording at identification points is the focus. Therefore, wireless data transmission with RFID can be viewed as a basic technology for some applications. Wireless sensor networks can also be used for objects that take on tasks such as data acquisition or data processing in addition to identification and data storage .

Sources and web links

  • M. Sedlmayr, A. Becker, U. Muench, F. Meier, HU Prokosch, T. Ganslandt: Towards a smart object network for clinical services. In: AMIA. Annual Symposium proceedings / AMIA Symposium. Volume 2009, 2009, pp. 578-582, PMID 20351921 , PMC 2815426 (free full text).
  • Rhea Wessel: German Researchers to Test Networking Tags for Assets, Blood. In: RFID JOURNAL. Retrieved June 21, 2020 .
  • A. Pflaum, M. Krupp: The intelligent perfume knows its neighbor - article surveillance with smart object technology . In: ISIS-AutoID, RFID special . No. 2 , 2010, p. 156–157 ( isis-specials.de [PDF]).
  • Alexander Pflaum, Jürgen Hupp: Sensor networks and localization methods as key technologies for the intelligent logistic environment of tomorrow . In: Hans-Jörg Bullinger, Michael ten Hompel (ed.): Internet of Things: www.internet-der-dinge.de (=  VDI book ). Springer, Berlin / Heidelberg 2007, ISBN 978-3-540-36733-8 , pp. 107-118 , doi : 10.1007 / 978-3-540-36733-8_8 .

Individual evidence

  1. ↑ Friedemann Mattern, Christian Flörkemeier: From the Internet of the computer to the Internet of Things . In: Computer Science Spectrum . tape 33 , no. 2 , April 1, 2010, p. 107-121 , doi : 10.1007 / s00287-010-0417-7 .
  2. ↑ a b Tomás Sánchez López, Damith Chinthana Ranasinghe, Bela Patkai, Duncan McFarlane: Taxonomy, technology and applications of smart objects . In: Information Systems Frontiers . tape 13 , no. 2 , April 1, 2011, p. 281-300 , doi : 10.1007 / s10796-009-9218-4 .
  3. ↑ Elgar Fleisch, Oliver Christ, Markus Dierkes: The business vision of the Internet of Things . In: Elgar Fleisch, Friedemann Mattern (Ed.): The Internet of Things: Ubiquitous Computing and RFID in Practice: Visions, Technologies, Applications, Instructions . Springer, Berlin, Heidelberg 2005, ISBN 978-3-540-28299-0 , pp. 3-37 , doi : 10.1007 / 3-540-28299-8_1 .
  4. ^ Weiser Mark: The computer for the 21st century . In: Scientific American . tape 265 , no. 3 , 1991, pp. 94-104 ( scientificamerican.com [accessed June 21, 2020]).
  5. ↑ The Internet of Things: Ubiquitous Computing and RFID in Practice: Visions, Technologies, Applications, Instructions . Springer-Verlag, Berlin Heidelberg 2005, ISBN 978-3-540-24003-7 .
  6. ↑ Elgar Fleisch, Günter Müller-Stewens: The influence of RFID technology on corporate management . In: Reinhard Hünerberg, Andreas Mann (Ed.): Holistic corporate management in dynamic markets . Gabler, Wiesbaden 2009, ISBN 978-3-8349-8787-7 , pp. 69-91 , doi : 10.1007 / 978-3-8349-8787-7_5 .
  7. ^ F Elgar Fleisch: What is the internet of things? An economic perspective . In: Economics, Management, and Financial Markets . tape 5 , no. 2 , 2010, p. 125-157 .
  8. ↑ a b Zoltán Nochta: Smart Items in Real Time Enterprises . In: Max Mühlhäuser, Iryna Gurevych (Ed.): Handbook of Research on Ubiquitous Computing Technology for Real Time Enterprises . IGI Global, Hershey, PA, USA 2008, ISBN 978-1-59904-832-1 , pp. 211-228 , doi : 10.4018 / 978-1-59904-832-1.ch010 .
  9. ↑ Alexander Pflaum u. a .: Deployment of a wireless sensor network to support and optimize logistical processes in a clinical environment . In: European Workshop on Smart Objects: Systems, Technologies and Applications . 2010, p. 1-7 .
  10. ↑ Gaby Neumann: Process management with intelligent logistics objects . In: Corinna Engelhardt-Nowitzki, Elsabeth Lackner (ed.): Batch tracking: possibilities, limits and areas of application . DUV, Wiesbaden 2006, ISBN 978-3-8350-9482-6 , pp. 73-92 , doi : 10.1007 / 978-3-8350-9482-6_5 .
  11. ↑ Michael ten Hompel, Lars Nagel: Cellular Transport Systems - Making Things Move in the “Internet of Things” (Cellular Transport Systems - Making Things Move in the “Internet of Things”) . In: it - Information Technology . tape 50 , no. 1 , January 1, 2008, p. 59-65 , doi : 10.1524 / itit.2008.0462 .
  12. ↑ Florian Kuzmany, Artur Luft, Razvan Chisu: The building blocks of the Internet of Things . In: Willibald Günthner, Michael ten Hompel (ed.): Internet of Things in Intralogistics (=  VDI book ). Springer, Berlin / Heidelberg 2010, ISBN 978-3-642-04896-8 , pp. 53-64 , doi : 10.1007 / 978-3-642-04896-8_8 .
  13. ^ W. Fu, YS Chang, MM Aung, C. Makatsoris, CH Oh: WSN based intelligent cold chain management . In: The 6th International Conference on Manufacturing Research (ICMR08), ​​Brunel university, UK, 9-11th September 2008 . 2008, p. 353-360 ( brunel.ac.uk ).