This paper describes the usage of object-oriented and microservice design patterns to enhance system maintainability. The project involved bringing together data from multiple sensor networks and providing single endpoint for client applications. The middleware consists of purpose-specific components, databases and various off-the-shelf IoT components. Key lessons learned include the role of design patterns in simplifying complex system interactions and improving understandability. The importance of a modular approach, where design patterns provide a structured framework that promote reuse of proven solutions and reduce technical complexity becomes clear during the implementation of the middleware.

Integrating scripting languages into Internet of Things (IoT) programming is attracting a diverse community of developers, including casual programmers who may not have the time or inclination to learn complex system programming languages and domain experts (e.g., web developers and machine learning researchers) who are familiar with these languages from their own fields. These languages alleviate the challenges of embedded programming for IoT devices with their simpler syntax, comprehensive libraries, and interactive debugging support. However, the performance overhead of scripting languages on resource-constrained IoT devices is a concern. This paper presents a comparative analysis of five IoT scripting solutions: MicroPython and CircuitPython (Python), Espruino (JavaScript), NodeMCU (Lua), and Statechart4IoT (statechart script). The evaluation focuses on computational performance, event responsiveness, and memory consumption. The results reveal their strengths and weaknesses and provide feasibility information for developers choosing suitable solutions.

The increasing significance of operating systems (OSs) in the development of the internet of things (IoT) has emerged in the last decade. An event-driven OS is memory efficient and suitable for resource-constrained IoT devices and wireless sensors, although the program’s control flow, which is determined by events, is not always obvious. A multithreaded OS with sequential control flow is often considered clearer. However, this approach is memory-consuming. A hybrid OS seeks to combine the strengths of the event-driven approach with multithreaded approach. An event-driven cooperative threaded OS represents a hybrid approach that supports concurrency by explicitly yielding control to another thread. Although this approach is memory efficient, as cooperative threads are not preemptive, it may not provide sufficient real-time performance. This article proposes a memory-efficient hybrid OS, called StateOS, for resource-constrained IoT devices. It is an event-driven cooperative threaded OS with partial real-time performance. StateOS implements a hybrid task scheduler that combines two cooperative threaded subsystems as kernel processes on a priority-based preemptive scheduler. This approach provides adequate real-time performance for IoT devices at a low memory cost.

This full research paper studies the significance of self-directed learning (SDL) in distance education. A literature review revealed many characteristics related to SDL that are important to success in distance education. The self-directed learning readiness (SDLR) levels of 124 students were gathered for this research, and the results were compared between contact and distance learners. The effect of gender on SDLR and the relationship between SDLR and preference for distance education were examined. There was no statistical difference in SDLR levels between women and men but indicators of self-directed learners’ preferences for distance learning were found. In addition, the SDLR scale scores between students’ degree levels were compared. The results support the notion that SDLR is related to maturity.

This Research to Practice Full Paper presents a comparison between a physical device and a simulator in a distance learning context. Programming embedded devices is very commonly taught using embedded hardware. One of the most used solutions is the Arduino microcontroller platform, which allows small embedded applications to be built and commanded in a programming language. However, there are some challenges in using physical devices for educational purposes. These challenges are particularly acute in distance learning or when the course needs to be scalable to a varying number of students. To address these challenges, we explored the potential of a simulator as a replacement for a physical device. We implemented the course using both the physical device and the simulator and collected student and lecturer feedback and experiences. The results showed that the physical device is somewhat more concrete and motivating, but the simulator is also very well suited for the purpose. The technical solution did not seem to have an impact on course completion or workload. There are also some advantages of using a simulator over a physical device, such as the possibility to test electronic connections without fear of breaking down the equipment

Locating the nodes of outdoor wireless sensor networks (WSNs) using (tri)lateration with a low-cost ranging technique, such as the received signal strength indicator (RSSI), often results in inaccurate location estimates. This can mostly be explained by the combined effect of distance estimate errors and localization geometry, both of which are subject to the reference nodes used. To develop techniques for reducing localization error, the distance estimate errors and localization geometry must be analyzed and taken into account. To address these challenges, this paper aims to seek ways to improve the quality of range-based trilateration localization for WSN nodes in varying outdoor conditions. Based on simulations, we analyze the effects of ranging error and localization geometry on localization error. For that purpose, we introduce a simple measure to evaluate the geometry of reference triangle (GRT). To improve localization accuracy and precision, we propose an adaptive range-based localization (ARBL) algorithm that is based on trilateration and reference node selection. In ARBL, the GRT values are calculated for each 3-combination of a preselected reference node set, based on which the combinations are selected. The algorithm exploits these reference node 3-combinations aiming to find the best ones at a given time using a selection criteria that is based on ranging error and localization geometry. The simulation and experimental results indicate that the proposed algorithm reduces localization error considerably. This shows that it is possible to achieve sufficient localization accuracy using range-based trilateration localization, even based on the RSSI in challenging outdoor conditions, by employing applicable techniques and information.

This paper describes the mapping of self-directed learning readiness (SDLR) for adult students applying for a master’s degree program delivered entirely as distanced learning. Since SDLR is strongly linked to both adult learning and online education, developing of self-directed learning (SDL) skills should be taken into consideration in our degree program. Making future students aware of SDLR is the first stage in introducing self-directed learning methods and practices in learning environments. The easiest way to do this is to have students answer an SDLR self-assessment questionnaire and give them feedback regarding their SDLR level. This paper presents how this is realized and provides the preliminary results of the study and the applicants’ SDLR score distributions. The results indicate high SDLR among all applicants.

For several years now, learning style mapping has been carried out for our students of the master's degree education in information technology. To better utilize learning styles in practice, a learning style module was integrated into the multimedia platform used in the education. The learning style module serves both the student and the educator. The goal was to create an application which, in the long run, would diversify the learning environment and make learning more efficient. This study describes the functioning and integration of the learning style application. The deployment of the application is monitored by collecting statistics of its use and feedback of its usability and usefulness from students and lecturers. In addition, the study presents the distribution of our students' learning styles.

This study examines the development of the education model created in connection with the Master Studies in Mathematical Information Technology. The model has developed from the first stage, where there was only face-to-face teaching supported with Learning Management System, to a stage where studying is possible also fully in online and students may choose themselves how much to take advantage of technology in their studies. The examination of the development of the education model is made from the viewpoints of accessibility, increased role of technology and interaction. In earlier studies, the education model has been evaluated for example from the viewpoints of changes in the participation rate and learning results, and the results have been positive. These viewpoints, in addition to describing the development path, will be highlighted in this study.

Many wireless sensor networks operating outdoors are exposed to changing weather conditions, which may cause severe degradation in system performance.Therefore, it is essential to explore the factors affecting radio link quality in order to mitigate their impact and to adapt to varying conditions.In this paper, we study the effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks.Experimental measurements were performed using Atmel ZigBit 2.4GHz wireless modules, both in summer and wintertime.We employed all the radio channels specified by IEEE 802.15.4 for 2.4GHz ISM frequency band with two transmit power levels.The results show that changes in weather conditions affect received signal strength.Of the studied weather variables, variation in signal strength can be best explained by the variation in temperature.We also show that frequency diversity can reduce the effects of channel-specific variation, and the difference between the transmit power levels.The rest of this paper is organized as follows.In Section II,

In this paper we present our experimental result of using wireless noise sensor network (WNSN) to detect road traffic. With the features implemented in our network such as multipoint measuring, synchronization, real-time data availability, and strict compliance of sound level meter (SLM) standard IEC 61672:2003, we assert the possibility of using WNSN to detect road traffic, such as vehicle amount, size, and velocity. This application can be extended and integrated as a part of Intelligent Transportation System (ITS).

Education providers aim to meet today's education requirements by employing, among other things, education technology solutions that increase flexibility. This has also happened with the master's level mathematical information technology degree directed to adults. In the degree program, lecture videos brought in together with face-to-face teaching provide good opportunities for flexible educational arrangements. Education with the help of videos can be arranged in such a way that students themselves will be able to choose their study mode in accordance with their needs. When students themselves can choose their study modes, many different ways to take advantage of the flexibility provided are created. It seems that students with different participation styles achieve the aims for their study progress in different ways. The purpose of this paper is to profile students with different study modes, the profiling being based on a structured questionnaire. In this way we try to find out what are the factors that affect the study mode. Our investigation focuses on both the effect of internal factors, such as motivation, and the effect of external factors, such as distance and time limitations, in the choice of a study method.