Till Örebro universitet

The paper focuses on the assumption that a sensor system for personal use has the optimal employment if coherent with the human perception system and provides redundant information by complementing sensors. Therefore, we provide argument for this thesis by demonstrating two examples within the quality indication of drinking water; two different electronic tongue sensors with similar operational principles have been used for making security assessments of drinking water in different environments, from tap, raw water and bottle. ©2008 IEEE.

In this article we present an approach to the design of human-like artificial systems. It uses a perception model to describe how sensory information is processed for a particular task and to correlate human and artificial perception. Since human-like sensors share their principle of operation with natural systems, their response can be interpreted in an intuitive way. Therefore, such sensors allow for easier and more natural human–machine interaction.

The approach is demonstrated in two applications. The first is an “electronic tongue”, which performs quality assessment of food and water. In the second application we describe the development of an artificial hand for dexterous manipulation. We show that human-like functionality can be achieved even if the structure of the system is not completely biologically inspired.

This paper presents a system where different scenarios can be played in a synthetic natural environment in form of a modified commercial game used for scenario simulation. This environment is connected to a command and control system that can visualize, process, store, and distribute sensor data and their interpretations within several command levels. It is specifically intended for mobile sensors used in remote sensing tasks. The system has been used in a disaster management exercise and there distributed information from a virtual accident to different command levels in the crisis management. The information consisted of live and recorded video, reports and map objects.

The problem of food- and water quality assessment is important for many practical applications, such as food industry and environmental monitoring. In this article we present a method for fast online quality assessment based on electronic tongue measurements. The idea is implemented in two steps. First we apply a fuzzy clustering technique to obtain prototypes corresponding to good and bad quality from a set of training data. During the second, online step we evaluate the membership of the current measurement to each cluster and make a decision about its quality. The result is presented to the user in a simple and understandable way, similar to the concept of traffic light signals. Namely, good quality is indicated with by a green light, bad quality with a red one, and a yellow light is a warning signal. The approach is demonstrated in two case studies: quality assessment of drinking water and baby food.

The use of remotely operated robotic systems in security related applications is becoming increasingly popular However, the direct teleoperation interfaces commonly used today put a large amount of cognitive burden on the operators, thus seriously reducing the efficiency and reliability of these systems. We present an approach to alleviate this problem by exploiting both software and hardware autonomy. At the software level, we propose a variable autonomy control architecture that dynamically adapts the degree of autonomy of the robot in terms of control, perception, and interaction. At the hardware level, we rely on the intrinsic autonomy and robustness provided by the spherical morphology of our Ground-Bot robot. We also present a prototype system for facilitating the interaction between human operators and robots using our control architecture. This work is specifically aimed at increasing the effectiveness of the GroundBot robot for remote inspection tasks

This paper focuses on the assumption that sensor system for personal use has optimal performance if coherent with the human perception system. Therefore, we provide arguments for this idea by demonstrating two examples. The first example is a personal taste sensor for use in finding abnormal ingredients in food. The second application is a mobile sniffing system, coherent with the behavior of a biological system when detecting unwanted material in hidden structures, e.g. explosives in a traveling bag

A sensor system suitable for measuring qualitative changes In the chemical and the bacterial content in drinking water is presented. The sensor, an electronic tongue, is based on a voltammetric technique and is therefore robust, simple and sensitive to small changes of water quality in the measured sample. The sensor system is constructed so the liquid sample will flow through the sensing unit while measuring continuously. The sensor has a solid construction, does not contain any fragile parts and is independent of how it is positioned. This creates new approaches and the sensor can easily be mounted on a underwater vehicle for continuous inspection of drinking water reservoirs and continuously monitor the quality of the water as well as be mounted directly on a drinking water tap.

The paper presents a relatively new human-computer interaction paradigm, where a human operator's perceptual actions are mimicked by the computer. In this sensor controlled system concept, we estimate a specific feature characterizing, for example, product quality, and apply intelligent analysis and an optimization to assess product quality as acquired by a human expert. The human operator contributes his/her intelligence to this man-machine interaction through learning the measurement system. An illustrative example shows how the human operator's knowledge and experience are learned by a sensor based system within a complex dough mixing optimization process in an industrial bread baking plant. The resulting sensor system acts as an intelligent feature estimator in a complex industrial process for monitoring the dynamical behavior there. The system allows easy sensor observation and makes decisions based on learning interaction with a human.

In the steel industry, there are many processes that include measuring and control of temperatures. With higher demand on quality, increased production, and effective energy consumption, the use of noncontact temperature measuring techniques has increased. After the cooling section in a continuous annealing-pickling line, the strip temperature is estimated by using the grey box technique. Temperatures are measured in the cavity between the strip and the roller using radiation thermometers. A model is made for estimating strip temperature using the measured temperatures and knowledge of the physics of the process.