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The increase of educational activities in automatic control, based on the use of virtual and remote laboratories, is already a fact. For that reason, it is necessary to include and update educational contents in agreement with the technological reality. This implies the development of methods to integrate new educational tools in the aforementioned laboratories in an easy, secure and flexible way. This paper shows how to integrate an educational tool developed in LabVIEW, widely used software, into the structure of our remote laboratory (LRA-ULE). The educational tool provides students with a control problem on a physical system where they need to design a PID regulator. They can also simulate its closed-loop behavior and identify the system in order to compare it with the theoretical model.

In this overview, we present an outline of the selected papers in these Proceeding on SWIIS 2000. Plenary papers IPL1, KNP2, SP1, and SSP are outlined first, and then all other contributions. Contributed papers are grouped according the respective topics in 7 chapters on: general aggression and security modelling; game theory and general systems approaches; fuzzy information, fuzzy systems and qualitative modelling; issues of ethics, fairness and justice in SWIIS problems; hybrid solution concepts and modelling techniques; case studies on Kosovo crisis; and business management based approaches. Due to the topic of special interest, the second chapter begins with the special survey paper. Individual chapters encompass two to four contributed papers.

This paper presents a new approach for the cross-directional basis weight control on paper machines. The multivariable control system with high-dimension is discoupled into several subsystems by introducing a new constraint on control variables to satisfy the computation and capability limitation of existing on-line control system. A block discoupling algorithm is developed, and a parallel control strategy is proposed to implement the control algorithm. Based on the strategy, a multiprocessors system is designed to realize the simulation. Simulation results show that the computational time can be significantly decreased and the real-time performance can be improved.

The aim of this paper is to present a methodology to design a generic Petri net based model for the class of paper mills finishing processes. This model is based on timed coloured Petri nets with decision solving procedures. This modeling tool is called by the generic term, high level Petri net. A special interest is given to represent the decision points of the system as conflicts in the net. The model is meant for simulation, to carry out qualitative analysis about the system. The purpose is to observe resource sharing and the consequences of different strategy choices on the production. Machine breakdowns, operation-machine allocation and times to change from one sort to another are taken into account. The basic concepts of the modeling tool and the methodology are first presented. Then, the characteristics of the class of processes are given. Finally, the generic model is explained.

We outline the needs for diagnostics in the paper industry and describe the state of the art. We have developed two next-generation diagnostic systems: WEDGE for the diagnostics of temporal variations, and FLEXPRO for spatial (cross-direction) variations. Both these systems combine powerful signal analysis tools with an intelligent user interface. Thus our systems can be used on a daily basis at paper mills, without an assisting process analysis expert. The flexibility of these systems allows easy adaptation to the continuously changing needs of a mill. Finally, we briefly discuss technological changes in papermaking which affect the diagnostics needs in the 1990's.

One main problem in dynamic system monitoring is to know over time in which physical situation the system is operating, in order to early anticipate possible failures. This paper addresses the problem of tracking a physical system and presents a model-based diagnostic system architecture, QDIAG, whose goal is to help operators early detect anomalies in dynamic systems in operation. QDIAG integrates both quantitative and qualitative techniques, using QSIM, Kuipers' qualitative simulation algorithm.

Drying is a very important phase of papermaking. Improving its economic operation is then of great interest. Recent process analysis techniques by modelling, identification and simulation offer new perspectives for such studies. This paper describes a mathematical model based on a theoretical analysis of the physical phenomena that occur in multicylinder paper machine drying sections. The main design and working parameters of these processes are taken into account and computer integration of the equations leads to an overall model of the sheet drying process which is easily workable. This model is the basis of a parameter estimation method which has been developed to evaluate the heat and mass transfer coefficient values in industrial equipment. Results from a pilot paper machine are discussed and the influence of some working parameters on the transfer coefficient values are shown.

Summary A multilevel approach to design of a paper machine control system has been presented. The system described includes not only regulating and coordinating control, but also on-line optimizing algorithms. In addition to being a convenient means for organizing the control activity, the multilevel approach provides a framework for organizing the computer software. In actual operating systems, the frequently executed first level programs are core memory resident, while the remaining levels of control reside in a rapid access drum mass storage. The core-drum memory combination is an economical way to implement multilevel control structures.

The paper discusses the r|ole of mathematical modelling in a context of development planning. Different planning functions are identified: opening-up questions, presenting alternatives, and providing plans of action. Each of these planning functions require different types of information and therefore different approaches to modelling

In this paper we develop an algorithm for estimating, in the presence of noise, cross and machine direction (CD and MD) moisture profiles based on a model described in the literature. The algorithm consists of a least squares parameter identifier for estimating CD profile deviations and a Kalman filter for estimating MD profiles. Simulation results of the algorithm are given. The preliminary results of the application of the algorithm to industrial data are also given. The algorithm developed can be extended to other measurement models

The development of algorithms for producing cutting schedules for the paper and board industry is reviewed. Three new algorithms are then presented for particular classes of problems. The first two purely heuristic algorithms permit explicit constraints on the number of cutting patterns and on the run-length. The third algorithm, which can be viewed as a heuristic algorithm set in a linear programming context allows implicit control of cutting patterns and run-length. These two difficulties have been the major limiting factor on the acceptance of routine computerised production of cutting schedules. It is argued that these algorithms and modifications based on the same basic approach will resolve all of the technical difficulties remaining.

Nearly 4 years ago in the field of Artificial Intelligence a learning machine called STeLLA was conceived. After three years of computer simulation of the machine in a variety of problem environments, the design is greatly improved, although the main features have survived. Since the machine is being simulated with a vehicle-steering control problem which is second order, non-linear and stochastic it would appear that STeLLA now qualifies for the title of “adaptive controller”.

It was of some surprise, after listening to all the contributions, to conclude that nothing had been said about the theory and application of extremum-seeking devices based on Evolutionary Operation EVOP and its associated modifications such as SIMPLEX and COMPLEX. In many real control systems the values of the measured variables are obtained at discrete intervals of time, which may be of the order of minutes, and consequently there may be considerable delay in the evaluation of the Performance Index. Many of the continuous-perturbation methods proposed at the Symposium do not lend themselves to systems of the former type, and it is thus desirable to be aware of alternative methods of control.

The control of bleaching and brightening reactions is important in the pulp and paper industry to ensure quality of the final product. This paper presents a review of the principal fundamental and practical aspects to consider when designing control strategies for bleaching and brightening operations. An approach is also suggested to minimize the operating costs of bleaching sequences.

Path Planning algorithms are indispensable in Autonomous Navigators. Though rover may not have prior information about the environment, path planning algorithms must be robust enough to navigate it to the target. A and D are grid based Path Planning algorithms which enable to reach the target in shortest path. Cost computations are fixed in A algorithm while re- computations are done in D algorithm, whenever new obstacles are identified. A modified version of D algorithm is presented in this paper where cost re-computation is done based on certain criterion. By reducing the number of times cost re-computation occurs, Modified D aims to produce shortest path similar to D algorithm with less memory requirements and execution time. This paper also brings out the implementation of A, D and Modified D algorithms with NXT LEGO Mindstorms kit and their evaluation in real time scenario. Comparison of the above algorithms is elicited.

The paper deals with unexpected behaviors and situations diagnosis for human-machine systems. Operator behavior is modeled using a nondeterministic discrete-event formalism and a specific model adaptation. An extension of pair algebra of partitions to nondeterministic finite state machines is used to develop the diagnosis method proposed in the paper. Possibilities of the proposed method are investigated and discussed. An illustrative example is provided, based on a tramway driving situation.

This paper deals with tracking of an airborne target with mechanically steered gimbal-mounted airborne radar. The objective is to keep the airborne target on the boresight of the radar antenna after the radar has gathered initial and less accurate information about the target via search mode. An extended Kalman filter is used to estimate the relative position, relative velocity and acceleration of the target in Cartesian coordinates. The estimates are used to generate line-of-sight (LOS) command angles, which are then used to drive the antenna beam to track the target. Realistic noise models of inertial navigation system (INS), radar, resolvers (to measure the orientation of the antenna), and antenna beam gyros are incorporated in the measurements. A high-fidelity model is developed to accommodate the sensors operating at different frequencies. Additionally, mathematical models of state vector initialization, process noise matrix and its initialization, measurement sensitivity matrix, antenna command angle generation and isolation of antenna from the aircraft's angular rates are formulated. A moderate manoeuvre is simulated and a comparison is carried out between the results presented in the literature and the model developed in the paper for a kinematic scenario.

This paper investigates the optimal estimation problem for networked control systems, where the control packets are randomly dropped without acknowledgement to the estimator. Most existing results for this setup are concerned with the design of controller, while the optimal estimation and its performance evaluation have not been fully studied. This paper shows, unlike many other cases such as intermittent observations or TCP-like systems, the system state follows a Gaussian mixture distribution with exponentially increasing terms. The optimal estimation is obtained by Gaussian sum filtering, while the computation is time- consuming. By constructing an auxiliary estimator, a fast and stable filtering algorithm is proposed to improve computational efficiency.

In this paper, we discuss the development of an Interior Point Method (IPM) solver for Second Order Cone Programming optimization problems that is capable of producing customized ANSI-C code for embedded, real-time applications. The customized code is generated for a given problem structure and makes use of no dynamic memory allocation, minimizes branching, wastes no mathematical or logical computations, and has minimal dependencies to standard libraries. The resulting software is designed to be easy to implement on embedded hardware with limited computing capabilities, while still providing accurate results rapidly enough for real-time use. The core IPM algorithm is a fairly standard primal-dual IPM, which makes use of Mehrotra predictor-corrector method with Nesterov-Todd scalings and Newton search directions. We make use of the Approximate Minimum Degree heuristic to maximize the sparsity of the Cholesky factorizations that are ultimately used to solve for the search directions. We conclude the paper by presenting the computational performance results from two example problems: a Mars landing optimal control problem and a reaction wheel allocation problem. The code generated for the Mars landing problem was successfully validated in three flights onboard a NASA test rocket, and was used in real-time to generate the optimal landing trajectories that guided the rocket. To the best of our knowledge, this was the first time that a real-time embedded convex optimization algorithm was used to control such a large vehicle, where mission success and safety critically relied on the real-time optimization algorithm.

This paper presents a method to address the pursuit-evasion problem which incorporates the behaviors of the opponent, in which a continuous-time Markov decision process (CTMDP) model is introduced, where the significant difference from Markov decision process (MDP) is that the influence of the transition time between the states is taken into account. By introducing the concept of situation, the probabilities addressing average behaviors are obtained. Furthermore, these probabilities are introduced to construct the transition matrix in the CTMDP. A policy iteration method for solving the CTMDP is also given. To demonstrate the CTMDP method for pursuit-evasion, examples in a grid environment are computed. The CTMDP-based method presented in this paper offers a new approach to pursuit-evasion modeling and may be extended to similar problems in the sequential decision process.

Apart from the 20-year anniversary in 2014 of the first publication of the GERAM (‘Generalised Enterprise Reference Architecture and Methodology’) Enterprise Architecture Framework, the timeliness of this paper lies in the new interest in the use of systems theory in enterprise architecture (EA), and consequently, ‘light-weight’ architecture frameworks (AFs). Thus, this paper is about the use of systems thinking and systems theory in EA and about how it is possible to reconcile and understand, based on a single overarching framework, the interplay of two major enterprise change endeavours: on one hand enterprise engineering (i.e. deliberate change) and on the other hand evolutionary, organic change. The paper also demonstrates how such change processes can be illustrated by employing systems thinking to construct dynamic business models; the evolution of these concepts is exemplified using past applications in networked enterprise building, and more recent proposals in environmental-, disaster- and healthcare management. Finally, the paper attempts to plot the way GERAM, as a framework to think about the creation and evolution of complex socio-technical systems, will continue to contribute to the society in the context of future challenges and emerging opportunities.

There has been a considerable amount of work done on tracking the boundaries of specified regions. The present paper focuses on the same problem. However, unlike previous works, this paper uses the cyclic pursuit scheme and its variants to locate the boundaries of specified regions, when the agents are initially deployed away from the region, and subsequently track the boundary continuously. The number of agents required under this paradigm is also considerably lesser than in existing strategies. In almost all cases, the algorithm described in this paper guarantees the convergence to the boundary. Simulation results have been presented to substantiate the efficacy of the proposed scheme.

The diffusion of visual sensor networks, and in particular of smart camera networks, is motivating an increasing interest on the research of distributed solutions for several vision problems. Specifically, in this paper we propose a distributed solution to the problem of reconstructing target positions in large Motion Capture (MoCap) systems. Real time reconstruction by means of centralized procedures is practically unfeasible for very large systems, while the use of distributed computation allows to significantly reduce the computational time required for reconstruction, thus allowing the development of real time solutions. Then the proposed distributed reconstruction procedure is optimized by exploiting information about the structure of the system: the visibility matrix states which objects in the scene are somehow measurable by a sensor (sensor-object matrix). Often, the typical localization of data from real application scenarios induces an underlying structure on the visibility matrix, that can be exploited to improve the performance of the system in understanding the surrounding environment. Unfortunately, usually these data are not properly organized in the visibility matrix: for instance, listing the sensors in a pseudo-random order can hide the underlying structure of the matrix. This paper considers the problem of recovering such underlying structure directly from the visibility matrix and designs an algorithm to perform this task. Our simulations show that the distributed reconstruction algorithm optimized by means of the estimation of the structure of the visibility matrix achieves an important computational time reduction with respect to the standard (centralized) reconstruction algorithm.

In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an efficient solution strategy for the unconstrained sub-problems that give the search-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This strategy combines a Riccati-like solver with the use of high-performance computing techniques: in particular, in this paper we explore the performance boost given by the use of single precision computation, and techniques such as inexact search direction and mixed precision computation. Finally, we test our HPMPC toolbox, a family of high-performance solvers tailored for MPC and implemented using these techniques, that is shown to be several times faster than current state-of-the-art solvers for linear MPC.

This paper describes an approach for compositional nonblocking verification of discrete event systems modelled as extended finite-state machines (EFSM). Previous results about finite-state machines in lock-step synchronisation are generalised and applied to EFSMs communicating via shared variables. This gives rise to an EFSM-based conflict check algorithm that composes EFSMs gradually and partially unfolds variables as needed. At each step, components are simplified using conflict-equivalence preserving abstraction. The algorithm has been implemented in the discrete event systems tool Supremica. The paper presents experimental results for the verification of two scalable manufacturing system models, and shows that the EFSM-based algorithm verifies some large models faster than previously used methods.

International audience; This paper deals with the problem of disassembly line balancing where partial disassembly and uncertainty of task times are studied. Few papers have addressed the stochastic disassembly line balancing problem and most of existing work focused on complete disassembly and have not considered AND/OR graphs. In the present work, tasks of the best selected disassembly alternative are to be assigned to a fixed number of workstations while respecting precedence and cycle time constraints. Task times are assumed to be random variables with known probability distributions. An AND/OR graph is used to model the disassembly alternatives and the precedence relationships among tasks and subassemblies. The objective is to balance workstations’ idle times, i.e. differences among stations’ loads are as small as possible. A stochastic binary program is developed. To illustrate the applicability of the solution method proposed, it was performed on on a set of problem instances from the literature.

based on the traditional machine vision recognition technology about human body movement trajectory, the paper finds out the shortcomings of the traditional recognition technology. By combining the three - dimensional depth data, the three-dimensional motion history image and the invariant moments of the three - dimensional motion history image computed as the eigenvector of body movements, the paper applies the method to the machine vision of the human body movements trajectory. In detail, the paper describes the algorithm and realization scheme of the human body movements trajectory recognition based on the three-dimensional depth data. Finally, comparing with the results of the recognition experiment, we verify that the method of human body movement trajectory recognition technology based on the three-dimensional data has a more accurate recognition rate and a better robustness.

In this paper, we present a distributed estimation setup where local agents estimate their states from relative measurements received from their neighbours. In the case of heterogeneous multi-agent systems, where only relative measurements are available, this is of high relevance. The objective is to improve the scalability of the existing distributed estimation algorithms by restricting the agents to estimating only their local states and those of immediate neighbours. The presented estimation algorithm also guarantees robust performance against model and measurement disturbances. It is shown that it can be integrated into output synchronization algorithms., Comment: The short version of this paper was published in Proc. IFAC World Congress, pp. 4662-4667, Cape Town, South Africa, 2014

This paper considers heuristics which can be helpful in reducing a workstations number in assembly line balancing problem. In the last sixty years a large variety of heuristics and exact solution procedures have been proposed to balance different structures of assembly lines. The author of this paper discussed some heuristics which almost lead to the reduction of the number of workstations (parallel single lines or u-line configuration) and productivity improvement. Special attention was given to the quality of final results. These are some measures of solution quality: line efficiency (LE), line time (LT) and smoothness index (SI) are calculated and compared. At the end final remarks are given.

This paper describes the use of scale estimators in field trials for mapping ground targets by an aerial vehicle with onboard sensing. Targets are assumed to be static and of a known shape. The vehicle is a lightweight, tethered, airship with onboard global positioning system, magnetometer, 3-axis accelerometer and gyro sensors, and a camera. The dynamics, trajectory, and sensing noise characteristics, are assumed a priori unknown. The paper focus on the use of scale estimators to minimize the influence of the outlier measurements in the mean and covariance of the target positions observed as the vehicle moves. The results obtained show an interesting performance, better than that obtained with common maximum likelihood mean and covariance estimators, namely a smaller uncertainty is achieved.

Design for Assembly (DFA) is a Concurrent Engineering constituent that gained a lot of attention due to fast and measurable benefits. The main principle of DFA is to foresee assembly problems at the design stage based on the experience regarding functionality, materials and machine availability. The work presented in this paper, named RFA - Redesign for Assembly, adds a way to explicitly register and retrieve experiences as part of the design process. It starts from an initial design, then RFA leads the designer through a detailed assessment towards an improved design according to previous experiences. Experience representation was done using a Group Technology classification concept that helps assign a primary-key for a Case Based Teaching underlying system. A supporting system has been implemented in order to try out RFA. DFA scholars have used RFA and proved that experience retrieval is easily and intuitively incorporated in the design process. The paper presents a study about the DFA methodology, reviews existing solutions (methods and software) from the literature and details the RFA architecture, implementation and tests. RFA shows potential for a new design culture based on knowledge sharing, but also, as a repository for a very valuable asset, i.e. problem-oriented assembly-related design experience.

The paper discusses the design process of a simple programmable logic controller. The conception of the PLC is presented. The idea is to develop PLC, which is compatible with EN 61131-3 standard. This part of standard refers to programming languages. However, instructions of the PLC are directly related to the hardware structure of the PLC. The most important part of the PLC is central processing unit and the paper especially focuses on this aspect. Instruction set, encoding and some elements of the design are presented and the paper is structured to show design flow from instruction list to a hardware design. The CPU was implemented in FPGA device.

The paper presents synthesis process of a hardware implemented reconfigurable logic controller from a ladder diagram according to IEC61131-3. It is focused on the originally developed a high performance LD processing method. It is able to process a set of diagrams restricted to logic operations in a single clock cycle independently from number of processed rungs. The paper considers the compilation of the ladder diagram into intermediate form suitable for logic synthesis process according to developed processing method. The data flow graph has been chosen for intermediate representation of a LD program. An original construction of the DFG with attributed edges has been described. It allows for efficient representation and processing of logic and arithmetic formulas. The set of compilation algorithms that allow to preserve serial analysis order and offer obtaining massively parallel processing unit are presented. The overview of a hardware mapping concludes the presented considerations.

In this paper an environmentally friendly bike messenger service with clients of different priorities is modeled using Markov chains. The aim is to examine how operation's resource availability provided to the clients can be optimized. The paper proposes a methodology based on reserving resources for higher priority classes. Based on data from a bike messenger company, the probabilities of each clients' class is optimized through a multi-objective optimization problem. The result is that the company, or a similar one, could use the proposed methodology in order to maximize its services levels.

Obtained in the space photos a ground resolution depends on a spacecraft spatial angular motion during optoelectronic survey. The paper studies case of optimal equalization of an image longitudinal velocity in the focal plane of telescope and tackles the problem of defining initial azimuth of the scanning survey under the condition of minimizing quadratic functional of image cross velocity values on edges of the CCD linear array. Results of a simulated survey of random surface object are presented, and the change of initial azimuth value for various survey angles within the swath is examined. The paper presents also a brief description of developed software for designing the space telescope characteristics, simulation and animation of the land-survey SC spatial motion and gives recommendations for its applications.

An explosion of digital multimedia technologies that permit quick and easy uploading of any multimedia file to the web, coupled with the rapid advancement of hardware and software have resulted in petabytes of multimedia data being available on the internet. In this paper, we provide a framework that rapidly integrates these data for personalized storyboarding utilizing Content Based Multimedia Retrieval (CBMR) techniques. A storyboard is a narrative of audio, text, video and images of a particular topic that are linked systematically. People have different abilities to understand a story/topic according to their learning styles coupled with experience, age, knowledge, gender etc. Personalized storyboard multimedia learning help the user dictate the learning process in a creative way through multiple means of representation, expression and engagement. This process involves active learning, both behavioral as well as cognitive. Learning is constructive, and information learned is remembered at a deeper level. The use of multimedia promotes meaningful learning that can be transferred or generalized to other situations. In this paper, various learning styles are discussed. The goal of the research was to design and implement a novel approach that integrates human reasoning with computerized algorithms for multimedia storyboarding for learning. By systematically coupling human reasoning and computerized process, we attempt to minimize the barrier between the human's cognitive model of what they are trying to storyboard and the computers understanding of the user's task. We present our model which utilizes a fusion of content based image retrieval, content based video retrieval, content based audio retrieval, and text based retrieval techniques with human computer interaction based relevance feedback to enhance the learning process through personalized multimedia storyboarding. To illustrate the advantages of this model in a greater detail, we showcased the concepts of this model utilizing the game of cricket. We summarize the paper by discussing the future in this area.

The realization of the software part of a safety-related system (SRS) is a challenging task due to the necessary verification activities. To assure that safety-related systems will offer the necessary risk reduction required to achieve the desired safety integrity level, the IEC 61508 standard defines requirements for the software safety lifecycle. The standard specifies verification activities associated with all phases of the lifecycle. In this paper, an approach to automate the verification activity with focus on the software part of SRSs is presented. Based on this, the software code, which is implemented using the IEC 61131-3 programming standard and the PLCopen specification, is automatically transformed to Uppaal formal models using a software tool called SA2TA (Safety Application to Timed Automata). To further automate the verification process, test cases based on equivalence class analysis and combination of states are generated utilizing the test case generator TCG. A laboratory real world case study is used to demonstrate the applicability of the proposed approach. The main contribution of this paper is the formalization approach of the application software behaviour in TCTL (Time Computational Temporal Logic).

The objective of assembly line balancing (ALB) is to assign tasks to workstations organized to perform tasks with precedence constraints. An important element of proper assignment of tasks to workstations is the consideration of skill requirement of tasks, and skill level of workers. This paper provides a general framework to model skill requirements and skill conditions for assembly line balancing models. Three types of skill constraints are defined. Low skill constraints determine workstations for workers who are able to perform only some simple tasks. High skill constraints consider tasks which require higher than average skills of workers. Finally, exclusive skill constraints consider situations where a group of workers is specialized in a subset of tasks. The paper summarizes the mathematical description of the different skill constraints, and shows how simple assembly line balancing models can be completed with skill considerations.

In the paper a method of using the Unified Modeling Language diagrams for specification of digital systems, especially logic controllers, is presented. The proposed method is based mainly on the UML state machine diagrams and uses Hierarchical Concurrent Finite State Machines (HCFSMs) as a temporary model. The paper shows a way to transform the UML diagrams to the form that is acceptable by reconfigurable FPGAs (Field Programmable Gate Arrays). The UML specification is used to generate an effective program in Hardware Description Languages (HDLs), especially Verilog.

Consequence reasoning is a major element for operation support system to assess the plant situations. The purpose of this paper is to elaborate how Multilevel Flow Models can be used to reason about consequences of disturbances in complex engineering systems. MFM is a modelling methodology for representing process knowledge for complex systems. It represents the system by using means-end and part-whole decompositions, and describes not only the purposes and functions of the system but also the causal relations between them. Thus MFM is a tool for causal reasoning. The paper introduces MFM modelling syntax and gives detailed reasoning formulas for consequence reasoning. The reasoning formulas offers basis for developing rule-based system to perform consequence reasoning based on MFM, which can be used for alarm design, risk monitoring, and supervision and operation support system design.

The article focuses on developing of a different and exciting project aiming to evolve and apply modern information and communication technologies in the presentation and promotion of cultural heritage. In the paper there is presented a system which provides detailed information about exhibits in museums through QR codes (Quick Response codes) and mobile devices. The activities, that take place during the creation of this system, are discussed. Technological challenges include an electronic database containing detailed information about the exhibits in the museum, the museum web portal, which will provide access to this information, QR generator, applications for mobile devices to scan QR codes. Also the implementation of a wireless Internet network is described as well as setting up connections with mobile devices. The paper presents the contribution that will help the implementation of such a project.