- The popularity of IoT has been growing rapidly in recent years. This is due to the reduction in the cost of devices that take place in IoT solutions, the creation of user-friendly software development systems and the development of cloud services. This, in turn, has led to the transition of the educational process to a completely different level, where higher education students can obtain most of the knowledge (both theoretical and practical) remotely without the need to physically visit the classroom. In this regard, a conceptual model of IoT hybrid laboratory is proposed, in which students have the opportunity to conduct their research both remotely and in patiently. The structure of the control system and general operating scenarios are described. The issue of optimizing the use of electricity in the proposed laboratories, which is associated with an increase in electrical load several times relative to classical laboratories.
The Internet of Things is a concept of building an environment in which static physical objects
(mechanical, digital, people, animals and other objects) are connected to the World Wide Web and
can communicate with each other and exchange information to solve everyday problems [
For such purposes, the concept of IoT is best suited, which will allow for mixed experiments in laboratories, with some students working with equipment and others conducting experiments remotely in parallel. The system fully controls the energy consumption and the turn of the experiments. This will save electricity in general in the laboratory and increase the number of students involved without increasing the physical presence of people.
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The implemented controller on the FPGA simultaneously works with the server and receives
commands, as well as, on the other hand, receives data from sensors, which are sent to the cloud using
the Internet protocol [
Another implementation of the remote laboratory [
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Another interesting implementation is the learning management system using IoT described in
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From the literature it is clear that there are two main areas of development of smart laboratories: the first is the so-called virtual laboratories, where all work with the equipment is performed remotely and students do not have direct access to the equipment, which in some cases is necessary, for example, when monitoring power equipment; the second - smart laboratories that provide comfort in a real laboratory and optimization of the workflow and electricity consumption. But they in turn impose restrictions on the number of students who can experiment with real equipment.
For example, if several research stands are connected to a specialized PC and the student uses only
one, then why is it not possible for another student to be able to use the free stand remotely.
Therefore, it is proposed to combine these two concepts and develop a smart laboratory where
students could work both permanently and remotely. In addition, the system should optimize the
energy consumption of such a complex. It is also advisable to use an artificial intelligence system for
the so-called deferred experiments, which is described below, as well as introduce into the system a
submodule of equipment accounting [
Given the previous work, it is proposed to develop the concept of a smart laboratory, which would combine the capabilities of a remote laboratory and a regular classroom for practical training. In addition, it would be advisable to integrate a system of control and management of electricity consumption by devices located in the laboratory. Due to the fact that such a concept involves complex management of facilities, it is proposed to use as a management manager the ANN apparatus, which would work in conjunction with the IoT cloud service. Figure 1 shows a simplified structure of such a laboratory. As can be seen from Figure 1, the system is divided into two subsystems - control of electrical appliances to ensure comfort in the room and control of training stands. These two subsystems are independent of data transmission and control channels.
The control subsystem of electrical equipment includes all the equipment that provides the educational process, namely the projector, air conditioners and laboratory heating, lighting and other equipment needed to ensure a comfortable learning environment in the laboratory.
In the current implementation, the control subsystem includes the following equipment: Smart projector for presentation of lectures or other teaching materials Smart Condition for air conditioning control and temperature control in the laboratory room. Smart Light - intelligent lighting control system in the laboratory
Additional control systems can be included in the current subsystem based on the wishes of lecturers and students or faculty management.
Each such device, such as a projector, according to Figure 2, is equipped with additional modules a smart meter for electricity consumption and a specialized relay to control the operation of the projector.
DB st Collecting data
DB usr
Collecting data Collecting data from labs kits Analysis user’s data Data analisis
DB st Collecting data
DB usr Collecting data The control subsystem of electrical equipment
Relay Projector 220V Smart meter
Relay Condition 220V Smart meter
Wi-Fi Wi-Fi control
data control data
Raspberry
GPIO 1 2 . . n
Raspberry
GPIO 1 2 . . n
Artificial Intelligent Data analisis Control 1 Collecting data from devices 2 Collecting data from labs kits 3 Analysis power consumption 4 Analysis user’s data 5 Make decisions 6 Control devices Smart Wi-Fi 220V meter PC
USB Arduino
Relay
Relay Smart Wi-Fi 220V meter
DC motor controler
PC USB V A A A V
Wi-Fi control data control The control subsystem of electrical equipment
Data collection from the SmartMeter and relay control is performed via a network control controller, such as a Raspberry Pi or BeagleBone board. Such a device serves as a gateway between the IoT service and the equipment. Its main functions include collecting data on the state of the equipment (data is read directly from smartmeters or from the cloud, or simultaneously) and control the inclusion of devices (commands from the local IoT service).
The subsystem of work with educational stands works on a similar principle. The stand consists of a PC, where the necessary software to remote access and communication with a debug board (in this case Arduino) or other controller is installed in accordance with the tasks of the stand, sensors and controls. For example, we will consider a stand for Investigation of the simplest DC circuits, the structure of which is shown in Figure 3. The stand includes a PC with software installed, board for getting electric values from investigated DC circuit, a set of sensors for measuring the current and the voltage, etc.
To measure the electricity consumed by the stand, a smart meter has been introduced, which sends data on the power consumption of the PC and the controller or the computer power control relay together with the stand. All data is collected and sent to a local cloud service where the student can see the measurement results. Communication with the local cloud service and the PC is provided by a secure local area network (Ethernet).
The local IoT service, presented in Figure 4, consists of the following subsystems: 1) user
database, which contains information about users and their access rights; 2) databases on measuring
equipment and experimental data for each user and stand separately; 3) apparatus of artificial neural
networks to control all elements of the laboratory in automatic mode [
The system also provides a global IoT service for working with remote users, the structure of which is shown in Figure 5. This subsystem has limited functionality. The system has user and device databases, as well as a data analysis system. That is, users can see the results of their experiments, perform data analysis and order a so-called remote experiment, when measurements will be performed only when the stand is vacated. In this implementation, the user will not have direct access to the equipment, but only pre-order the experiment according to the configuration specified by him.
This layout enables dividing the work process in the laboratory and ensuring the security of the
whole complex [
In addition, learning should take place where students spend the most time. Today it is social networks. The introduction of social networks [26-28] in a smart laboratory will allow first of all the placement of a variety of materials: Announcements - a function when it is necessary to inform as many students as possible in a short time about changes in the educational process (change of class schedule), competitions, Olympiads that will take place in the near future; Survey - allows you to take into account the wishes and suggestions through various surveys; Photo album - a function that allows you to place educational material in drawings, illustrations, photographs. This is necessary in order to speed up and facilitate the assimilation of educational material; Video - this feature allows you to demonstrate the experimental basis for the learning process; Materials for learning - diagrams, tables, text material, interesting facts, etc. (everything that reflects the subject of study).
The social network allows the teacher to better remember students (correlate names and faces in the audience), understand their interests and allows them to jointly create and improve the course. Instead of simply consuming information, students become developers and experts in a virtual learning group environment (creating messages, discussions, resources, and more).
Thus, the use of social networks can give the learning process more interactivity, positively affect the results of cognitive activity of students, become an effective means of increasing motivation and quality of learning, organizing teamwork, joint project activities, individualize the student's virtual learning space.
The stand (see Fig. 3) includes a PC with the following software: LabVIEW [
A classic voltage divider circuit is proposed as a research electrical circuit (Figure 6)
The stand is based on the previous scheme and includes the following components: 1. controller of data collection from sensors and supply voltage control. In this particular implementation (Figure 7), an Arduino board is proposed, but you can also use another module based on different microcontrollers; 2. analog current sensor Arduino 30A ACS712 on the Hall effect; 3. analog voltage sensor (V1 ... V3); 4. variable resistors R1 and R2 based on digital potentiometer X9C103S.
The essence of the experiment is to experimentally check the basic relationships of electrical quantities for DC circuits with series connection of resistors. Student Increasing the value of one of the resistors from 100 * (Number of students) Ohm to 200 Ohm in 20 Ohm steps, fills in table 1.
In addition to this, the program transmits data to a foggy service for remote access and control. There are two options for working:
1. When a student conducts an experiment locally, the control interface on the fog service will become inactive and will be asked to stand in the queue for the experiment, although the process itself will be visible to other students.
2. If the control and experiment are removed, the main interface on the PC will also become inactive and the student will be asked to enroll in the queue or select another free stand in the laboratory.
All parameters will be collected by the Arduino board and transferred to the PC, from where, after pre-processing (if necessary), they are transferred to the local IoT service.
The control system of the PC itself includes two devices: 1. DELOCK 25242 power supply control controller: ATX Power Supply Controller or its analogue, which will be connected to the Raspberry Pi (see Figure 2);
2. smart current-consumption meter smart-MAC [
This information is needed to analyze the total power consumption of the laboratory stands and to further intelligently control the PCs and stands described above, as well as to automatically control the on / off and start of the PCs themselves.
From the above structure of the system (see Fig. 1), the laboratory must have many scenarios for working with users and operating scenarios. In addition, the structure and algorithms of work in this system should be divided into two main classes - algorithms of the subsystem of control of educational equipment in the laboratory and algorithms of software operation of test benches, where research will be conducted (Fig. 9).
The main functions of the control system of educational equipment include: control of equipment operation, equipment management, collection of data on the use of equipment, collection of energy consumption statistics of classroom equipment for each device separately and in total.
Below is a scenario of the projector, which is located in the laboratory. The main controller of the projector control is a script that operates on a local IoT service and has access to a database of schedules in a particular laboratory, where it loads the time of laboratory, also downloads presentations of laboratory classes, if already downloaded by the teacher. If (before a certain lesson the teacher) did not download the presentation files, the system simply turns on the projector in standby mode relative to the schedule, and the teacher can use the Web interface to download the presentation or directly connect to the projector and give a presentation. In parallel with the projector works a smart electricity meter, which sends data on energy consumption by the projector. These data are collected on the local cloud service for further analysis by the laboratory administrator (if necessary), as well as for reporting to the accounting department.
In this paper, the authors proposed a conceptual model of a training laboratory based on IoT, which combines the functions of a remote laboratory and a regular classroom for practical classes. The general structure of such system and the basic modules of functioning are presented.
Despite the fact that only one test bench is described, it is planned to implement about 10 test benches for each PC (see Figure 1) for different types of tests.
The subsystem of control and management of electricity consumption by the equipment working in the laboratory and the scenario of operation of measuring stands is described. Scenarios for managing objects in this system and working with users are revealed.
In further works, the authors plan to implement the main modules of the system and the use of Artificial Neural Networks for intelligent control and protection of the system as a whole.
The authors would like to thank the Ukrainian-German Education and Research Center of West Ukrainian National University for the opportunity to use their training laboratories and support from the Internet of Things project: Emerging Curriculum for Industry and Human Applications ALIOT (573818-EPP-1-2016-1-UK -EPPKA2-CBHE-JP) for the provided equipment for measuring stands.
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