A smart data logger system based on sensor and Internet of Things technology as part of the smart faculty

1. Introduction

Microclimatic (ambient) conditions have a great impact on the working environment. In order to be able to develop a smart faculty system, it is necessary to develop a smart system that would independently monitor and control the work environment with an emphasis on microclimate conditions. Based on such a system that would control ambient conditions, systems could later be developed that could use this data to automate the college premises. In other words, if the schedule of instruction is known, as well as the number of students attending the class, it is also possible to determine the rooms that will be used for lectures, ie practical classes. When all of the above has been harmonized, it is necessary to adjust the ambient conditions to provide the best possible conditions for the classes. To enable these conditions, it is first necessary to monitor certain microclimate parameters such as ambient temperature, humidity in the lecture rooms, ambient light, air quality, etc. Based on the measured data, a certain system within the smart faculty can itself remain responsive and create the most favorable conditions for lectures. This means that if the smart faculty system knows how many students are arriving for a fixed hour, based on temperature, ambient lighting, etc., the classroom or amphitheater can be independently ventilated, the room heated or ambient lighting increased, all depending on the microclimate conditions.

Devices such as smart data logger systems can be used to expect as part of smart faculty, also in the laboratory, library, botanical gardens, etc. It is known that productivity depends on ambient parameters. Based on these parameters, the boundary conditions for the workspace are defined separately [1]. For example, in schools, faculties and laboratory, the optimal temperature for workspace is above 21°C (69.8°F) [2], when is the highest productivity (100%). With a change in temperature for one degree, the working concentration is also changed by 3% to 5% (decreasing). For the same workspace, the light intensity is in the range from 200 lx to 400 lx. Other parameters are also defined, such as air humidity, atmospheric pressure, carbon dioxide (CO₂) concentration, etc.

To maintain productivity at the highest level, it is necessary to maintain the working conditions within optimum values. In order to do this, it is necessary to control the temperature, humidity, light intensity and air quality in the operating environment itself. Control of these parameters is carried out by ventilation, heating or cooling of classrooms, offices, etc., as an increase or decrease in the intensity of lighting. Accordingly, it is necessary to react in a shorter period, so that changes do not significantly affect working productivity. For this reason, it is necessary to implement a system that will independently monitor, measure and react on changes in ambient parameters, or react in a timely manner (on time). One such system is described in this manuscript. A smart data logger system can be observe, measure, store measured data and react when that is necessary. It includes wireless communication, smart sensor technology and Internet of Things technology. This system includes the wireless communication technology and Internet of Things technology as in research [3–5].

Earlier research [6] was based on measuring ambient/atmospheric parameters and storage it on Security Data (SD) card that cannot be accessed during the measurement to give the end user an insight into the current results. Research [7] was based on wireless communication and storing measured atmospheric/ambient parameters in commercial Cloud or database with commercial data protection. In research [8] the smart house system based on Internet of Things was described. Both works were related to smart weather station/home systems that are designed to monitor and measure both atmospheric and/or ambient parameters. Unlike the research [7], the research [8] monitored the ambient parameters (temperature and LPG gas concentration) based on the changes the system reacted, including ventilation/room cooling or heating in case the temperature was lower than the set value. A system that can be implemented into a smart faculty system is another earlier research [9]. The topic of that research dealt with a smart system for monitoring attendance at classes. Student attendance was stored online in a database so that professors had an insight into the level of attendance at their classes.

Smart data logger system is intended to, in addition to monitoring and measuring ambient parameters, respond following the changes in the parameters being measured. So if the temperature value is not within the optimal range, the cooling or heating unit is switched on, depending on the temperature change. It is similar in the case of other ambient parameters that are monitored, or measures. The user can track the results of the measurement in the private database using a computer or via a mobile application on a smartphone. This realized database is much more reliable from the data protection angle. Reliability is reflected in the fact that the database has access only to the user via username and password, and also the entry is only allowed to the allowed clients. It is also possible to further protect data by using encryption/decryption techniques.

Sending the measured parameters to the database is possible using Global Radio Packet Service (GPRS) or Wireless-Fidelity (Wi-Fi) communication. Global Radio Packet Service is mainly used in cases where the data logger system does not have access to the Internet in premises (offices, classrooms, warehouses, etc.) where measurement is performed. Given that in the present time there are offices, classrooms, even warehouses, there is Internet access, it is possible to use the Wi-Fi communication. In this way, the user is not bound to monitor the account balance on the SIM card in case of using Global Radio Packet Service communication.

The device has a wide application based on ambient parameters that measure: Temperature [°C] or [°F], Humidity [%], Atmospheric pressure [mBar] or [hPa], Lighting [lx], Detection and measurement concentration of carbon dioxide (CO₂) [%].

All measurements are accompanied by information on the time and date of measurement. The period for reading the ambient parameters and storage in the database can be set within the range of 1 to 20 minutes, depending on the need for monitoring and measurement of parameters. For the user to monitor the values of the measured parameters, the smartphone application has been implemented. By using the application, the user monitors the results of the measurement, and the application also offers the ability to control the ambient parameters being measured. Control nodes are used to control ambient parameters, managed by a control unit that serves the whole system. They turn on air conditioning or ventilation if temperature, relative humidity or CO₂ control is performed, or adjust the brightness intensity by controlling windows blinds or by turning on the lights in the room. Based on the measured parameters, the application sends a message to the control unit which parameter needs to be regulated, or to regulate the values of that parameter to be in the optimal range.

2. Theoretical background

The so-called “Industrial Revolution 4.0” has the greatest influence on the development and take-up of primates by “smart” devices. The field of application of smart acquisition systems is very wide. Examples of these systems include smart faculties, smart homes, smart industries, and even smart cities. All these examples are based on self-monitoring, measurement and response to the change of certain parameters.

The inspiration for the implementation of this system is reflected in the need to monitor the microclimate conditions in the faculty premises and to manage the systems, thus creating a better working environment. The research gap we encountered during our research to solve this problem led us to implement a system that would respond independently depending on ambient parameters and control the work environment. As the research progressed, we concluded that such a system provided several opportunities that we did not encounter when researching similar papers published in reference journals.

Realized system provides an opportunity for further implementation in other faculty rooms where smart faculty service could be implemented. Which would be reflected in the following: monitoring the microclimate (ambient parameters) in classrooms, amphitheaters, monitoring attendance at classes (which was the topic of earlier research) [9], as well as teaching schedules, which would allow the classroom itself to adjust the conditions to suit the group of students coming to class next.

Another scenario of integration into the smart faculty system would be to integrate the realized system with student services, where the student service know how many students go to the colloquium, so the classroom itself can be ventilated, set the temperature, etc. and prepare for the colloquium following the expected conditions of use.

A smart data logger system is essentially a system for tracking and collecting data based on ambient parameters and stores them in a Cloud or database on a web server [7]. Also, based on the same, it reacts in such a way that the values of the ambient parameters are kept in optimal values (by activating the ventilation, heating, turning on/off lighting, etc.). Data acquisition and control systems such as the smart data logger system are based on Internet of Things technology. Systems that are known as “smart” can be called smart, unlike those “non-smart” systems that are not autonomous and that require human factor to operate. Non-smart data acquisition systems use only wired connected media to store measurement results, such as Security Digital (SD) card memory, flash memory, EEPROM memory, etc.

Main parts of the smart data logger system can be divided as [7]:

The main challenge to be fulfilled by a device such as the smart data logger system is how to realize a smart data logger that will be as cheap as possible and as safely as possible to store the measured data and to react at the right moment so that there will be no large oscillations in the values of the measured parameters.

Smart data logger systems have many different implementations, which can be reflected in the way in which communications, storage, and control are realized. Most of the smart data logger systems have implementations that use wireless technologies between the sensor part, the main unit and between the main unit and the control unit. Based on the above, the smart data logger systems can be realized using different technologies, such as [7]:

Smart data logger systems most often use wireless internet communication for their work, more precisely to send data. As a storage medium, Cloud (CloudMQTT, ThingSpeak, etc.) or a database on the webserver is used. What is common in most smart data logger systems is the following:

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Fig. 1.

Block schematic of the smart data logger system.

It is important to note that smart systems based on RF and Bluetooth communication are limited by short range. Accordingly, the authors are in the manuscripts [10,12–14,17,18], use communication modules such as ZigBee [10,17,18], characterized by a small range (10–100 m, depending on location and working environment). Systems that use the LoRa communication platform [13] also are limited by range. In manuscripts [14] authors use Bluetooth communication for one of the ways of realization of systems. The authors of [17] used RF communication, which in no way provides the ability to communicate with the Internet, but communicate with a PC, from where the user further manually sends data to the Internet. Compared to the above, our system has the ability to autonomously store the database with measured parameters, which is one of the advantages of the system. The authors investigated in manuscripts [11,16,17], the use of Arduino platform, which is not the most reliable for the implementation of serious acquisition systems, because Arduino is an open-source-based system, unlike the PIC microcontroller which is used for realization of our system, which is another benefit of our system. On another side, authors in [11,12,16], use commercial Cloud services for storing data, which are characterized by commercial (low level) of data protection. The smart system described in this manuscript store data in the database with a few levels of data protection, starting with user identification, to allowing which data will be stored into the database. Regarding to the sensors used to realize smart data logger systems, authors in [10,18] use analog sensors. More specifically in [10], an analog photodiode-based sensor was used to measure the light intensity, unlike the digital sensor used in our system, which is characterized by high resolution (0–65535 lx). On the other hand, in [18], the authors used an analog sensor to measure temperature, which with the platform used provides a lower resolution of measurement than the digital sensor used in the implementation of the smart system we implemented. Although not an allogeneic sensor, in [10] the authors used a sensor of lower resolution (in the range from 9 to 12 bits) for measuring temperature, relative to the sensor used in our manuscript (20 bits of resolution – BME280). In [10,15], the authors provided explanations for results based on results obtained in laboratory conditions, which is not the most relevant to the results obtained by using our system in real conditions. In accordance with the measurement results, the authors in [11,12,16,18], presented the results based on the measurement in just a few minutes of, up to several hours (12 to 24 hours) measurement, for unlike the results obtained in our case, after 8 days of active measurement. In [10,15], the authors did not even give the results of their measurements, based on which they gave explanations of their systems. In terms of system power supply, it should be mentioned that in [13,14,17], the authors used battery-based or solar-powered power supplies. This type of power supply is characterized by short working life since the communication modules consume more energy when sending data than in the idle state, or when measuring. In this way, these systems may at the crucial moment fail or make the measurements irrelevant if the supply voltage level is lower as the battery capacity decreases. Unlike those systems, our system uses 12 V. Since in our case the system is used indoors and also [14,17], an additional advantage over these systems is that our system does not require sunlight as the batteries recharged. In [15,17], the platforms on which the implemented system is based are not clearly defined, which is not the case in our work, where both the platform and technical documentation of the components used are clearly defined, and an electrical diagram is provided, which is not the case in [10–18]. Some of the works cited do not have clearly defined platforms on which data is stored. In the mentioned works, there are no actions after the measured values, unlike our system.

The basic idea of the Internet is to enable data collection in-situ and send it and present it on the Internet. A large number of commercial services (free Cloud platform), as well as especially realized databases on private servers, can be used to store data. In the case of free commercial services, it is necessary to note that they offer a low level of data protection. For this reason, it is necessary to use either paid commercial services or to provide a private service on the server for data protection. Smart things such as smart sensors are connected to the Internet and can automatically transfer data without relying on human interaction – hence being “Machine to Machine” (M2M) interaction [19]. A Machine to Machine talk (M2M) system maybe generally seen as a wireless sensor network where sensor nodes are embedded systems referred to as M2M terminals. Embedded software running inside M2M terminal should manage concurrent tasks efficiently and reliably within limited hardware resources and with real-time constraints.

In this manuscript the model of smart data logger system based on PIC microcontroller and Internet of Things technology is described. The system is designed to be scalable and easy to setup and extend, and also reliable both in working and data protection. It is based on powerful PIC microcontroller which manages the whole data logger system. It includes embedded sensors for observing and measuring the environment or places where necessary and GPRS module which uploads data to the database in the webserver. Also, the system includes nodes for control ambient parameters, when necessary.

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Fig. 2.

Electrical scheme of the smart data logger system.

3.2. Implementation (hardware and software)

Realization of the control unit for measurement system can be seen on electrical scheme of the smart data logger system shown in Fig. 2. The microcontroller used for the realization of the data logger, operates at a frequency of 32 MHz, using an internal oscillator. Used microcontroller has 2 USART (Universal Synchronous Asynchronous Receiver Transmitter) modules [26]. Also, PIC18F45K22 microcontroller has 2 modules for communication protocols via the I2C or SPI bus. It is necessary to note that the used microcontroller have hardware realized I2C and SPI bus communication pins, but from the other side, I2C and SPI bus can be realized using software, which is the case in this manuscript. As previously stated, the BME280 (BOSCH Sensortec) sensor was used to measure temperature, relative humidity, and atmospheric pressure. Communication between microcontroller PIC18F45K22 and BME280 sensor is realized via the I2C bus [27]. The used BME280 barometric sensor provides a wide range of measurements:

Air humidity from 0% to 100% RH.

Temperature from −40°C to +85°C.

Atmospheric pressure from 300 to 1100 [hPa] or [mBar].

Also, there are a Real Time Clock (RTC) module DS1307 [25], which is used to set the current time and set the measurement step. DS1307 module is used to set the duration time of the measurement. The Security Digital (SD) memory card is used to store data in case the system does not have access to the Internet. The connection with the microcontroller was realized using the SPI protocol. The data stored during the measurement is accompanied by information on the measurement time, for the user to have an insight into the results and when it was not possible to store the data in the database on the webserver.

Measurement of illumination (light intensity) is done by the sensor BH1750 (ROHM Semiconductor), which for communication with the microcontroller uses the software realized I2C bus, such as BME280 sensor. The used sensor provides a wide range of high-resolution measurement in a range from 0 to 65535 lx with 0.5 lx resolution.

An MQ-7 sensor was used to detect the concentration of carbon dioxide (CO₂). This sensor provides the possibility of digital and analog output. In this case, an analog output was used and therefore, a pin of microcontroller RA.1 was used to communicate with this sensor, which is software-defined as an analog pin. At port A, the microcontroller has an A/D converter, which is used to determine the percentage or concentration (in ppm) of carbon dioxide (CO₂) in the environment. The MQ-7 sensor also offers wide applications, i.e. possibility to measure several different parameters, such as hydrogen – H₂, oxygen – O₂, methane – CH₄, carbon monoxide – CO, etc.

The GSM/GPRS module SIM800l serves to send data to the database realized on the webserver. Also, the SIM800l module serves to send an SMS to the user with information that the measurement has been completed. This module communicates with the microcontroller via the (RX/TX) UART serial module using AT commands [28]. The system checks for each sending whether there is a connection to the Internet, or whether the GSM module is registered to the Internet as a GPRS module. If the module response is that at that moment it is impossible to make a connection to the Internet or database, the data is stored on the Security Digital memory card. The data on the Security Digital memory card is stored in a previously created file. The buttons to adjust the operation of the Real Time Clock module are also used to create a name for the file in which the measurement results will be stored.

To interact with the user while working with the smart data logger system, a 4 × 20 character LCD display is used [29]. The LCD display serves to monitor the current measurement results when the system does not have access to the Internet when the results are stored on the Security Digital memory card.

Security Digital memory card (realized as Security Digital memory card reader module) are communicate with microcontroller via SPI bus, connected on port D of microcontroller (SPI clock (CLK) – RD.0, Master Output Slave Input (MOSI) – RD.1, Master Input Slave Output (MISO) – RD.2 and Slave Select (SS) – RD.3, respectively).

The power supply of the device is realized by DC power supply (5 V–12 V). The control nodes that activate the devices for controlling the ambient parameters that are monitored and measured, use the power to which the inbound control devices are controlled. It is important to note that for the operation of control nodes, AC voltage (220 V) is required to be converted into a DC voltage of 5 V for the operation of control nodes.

When starting the device, a selection of the language will be used, which will be used for further adjustment and operation. Then follows the time setting, which consists of the following:

Setting the current time when the measurement starts.

Setting the time when the user wants the smart weather station to complete the measurement.

Setting the period of measurement, i.e. send data to a database in the webserver.

When the measurement starts and stop time as well as the measurement period are set, then enter the user’s IP address of the database in which the measurement results will be stored.

Next, the user needs to set the name of the file on the Secure Digital memory card in which the measurement results will be stored, for the case the system does not have Internet access. After that, the number of the phone to which the SMS (Short Message Service) is sent at the end of measurement will be entered.

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Fig. 3.

Basic algorithm of the embedded software of the smart data logger system.

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Fig. 4.

Realized device: a) printed circuit board and 3D model, b) front and c) rear side of the device.

Finally, check all settings, i.e. information to the user about the entered IP address of the database in which the results of the measurement will be stored, so that at the end of the setup the countdown begins before the start of the measurement. Each thread during the work of the smart data logger system is defined as shown in Fig. 3 as the algorithmic mode of displaying the software. The Main thread is responsible for starting the other threads. It also sends diagnostic messages to the LCD display and receives simple commands from the keyboard, affecting the application’s execution flow (e.g. stop, restart, etc.).

The Main thread contains all the settings necessary (e.g. settings of A/D converter, the values of registers for the sensors that work through the I2C bus, SPI settings for Security Digital memory card communication, and the file name for backup data storage) for the proper operation of the smart data logger system. Also, this thread contains the settings of the measuring time (start/stop) and the period of measurement that will be sent to the Measurement thread. The Measurement thread receives settings from the Main thread before start measurement. This thread is used for the acquisition of the measurement results from the sensors, storing them in the variables (variables are defined for each parameter that is measured separately) through Transfer thread.

The Transfer thread transfers data from sensors to the microcontroller (from A/D converter, I2C bus). When data is transferred to the Main thread from sensors, the data must be processed before sending it. All data of the Integer type must be converted to the String data type and then with the defined IP address and packet length send to the Send thread.

In the Send thread, converted data and necessary parameters for the database (IP address and packet length) are concatenated into one String data. The GSM/GPRS module must be configured to work as a GPRS (wireless Internet) module using AT commands to send data to the database in the webserver. Data from the smart data logger system is sent via Message Queuing Telemetry Transport (MQTT) communication protocol, such as going to a web page and filling out a form.

This communication happens through plaintext, JSON or XML. If the system does not have Internet access, measured data will be stored in the created file on the Security Digital memory card. It is possible to use local storage like a PC through USB communication and software application and flash memory as an alternative.

Figure 4 shows the appearance of the printed circuit board (PCB), as well as the 3D model of the realized device (front and rear side). It can be seen upper and down layer with component distribution. This device was developed in the same way as the previous device we developed for educational purposes [30].

The 3D model of the printed circuit board of the device is given in the Fig. 5.

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Fig. 5.

The 3D model of the printed circuit board.

3.3. Usage scenario

During the measurement, the user is able to see the remaining measurement time on the LCD screen, i.e. how much time is left until the end of the measurement, in the form of a progress bar, followed by information in percentages. The measurement interval is 20 minutes (adjustable). Also, the user is able to see on the LCD screen the remaining time before the next measuring and sending measured data to the database.

When each measurement cycle is performed, it is necessary to convert the results from the integer type into the String data type. Converted data using the GSM/GPRS module is forwarded to the Internet and placed in the database.

At the end of the measurement, the message on the completed measurement is printed on the LCD display, the device sends a text message using the GSM module. The user will receive an SMS on the completed measurement on his mobile phone, whose number was previously entered during the system setup. The message text will depend on the previously selected device language.

In order to have an insight into the results of the measurements stored in the database, the application for the smartphone was realized. By using the application, the user can access the measured and stored data in the database at any time. The method of displaying the measurement results is in the form of charts, where each of the parameters is displayed on a separate charts. In addition to the graphical presentation of the data, the charts also show numerical values for each displayed point.

In addition to being smart, i.e. being capable to collect and store data and manipulate the environment without human involvement. It is important that the system provides means for observing/tracking collected data and informing end-users of any unusual behavior, for example, sudden changes or values beyond the boundaries. Such services may be implemented as part of separate mobile or computer applications. It is recommended that such applications be developed for mobile operating systems.

Such an application would follow component and data-flow organization as shown in Fig. 6. The core functionality is pulling data from the server and displaying it in some meaningful manner, e.g. linear/bar/pie charts, statistics, etc. It could also send notifications if any variable expresses unusual behavior.

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Fig. 6.

Component diagram, core functionalities.

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Fig. 7.

Results of measured data: a) amphitheatre A3 in the last 24 h, b) laboratory 327 in the last month.

Furthermore, it could provide means of altering environmental conditions, e.g. defining the desired temperature so that the system can activate its heating/cooling unit accordingly. First, there has to be communication established between the application and the server in order to access its database. It can be achieved using HTTP methods. Data pulling can be done in various ways, using several methods, depending on the development environment, libraries and databases used. Few of those methods are:

Database polling: It consists of periodic checks to establish if a database has new data inserted. Although it is very easy to implement and commonly used, it has a few drawbacks. Depending on the frequency of polling, the application can spend a lot of time establishing and maintaining connections to the server, as well as sending requests which take CPU time and resources. It also leads to increased battery usage that can negatively impact mobile devices. Taking into account these drawbacks, it is recommended to implement this method on a separate thread and use it in case of frequent insertions into the database – a few seconds apart.

Messages, notifications: This method utilizes database triggers, i.e. when insertion happens, the trigger activates and notifies application. The application is only active when there is new data available. In some cases, depending on the database used, this method raises security issues that have to be maintained.

The best way to display metric data for a user would be a graphical representation, using different diagrams, e.g. linear, bar, pie chart. There are numerous libraries that allow such data presentation, depending on the development environment, the desired look and functionality. One of these libraries is MPAndroidChart [31], which is used in the realized demo smartphone app for Android, as shown in Fig. 7. It is also important to allow users to view multiple monitoring stations, as well as the different time periods during which measurements were made. A statistical overview is also of great importance because it can provide valuable information. One of the advantages of smartphones over computers, mentioned in this article, is the ability to display notifications even if the application is not active. One of the ways of achieving this functionality is using Android Services [32], which was used in the demo application.

This functionality was realized in a way that enables users to define custom boundaries, shown in Fig. 8a. This service, running on a separate thread, would constantly check if newly measured values are within those boundaries. If not, the application displays a notification, e.g. a warning. Additionally, this application allows users to send commands to the system in order to change environment parameters according to the user’s will, as can be seen in Fig. 8b.

The application provides the ability to monitor real-time measurement results as well as control them. The presented system was realized for the monitoring of several amphitheaters and laboratories. In this regard, the application allows the selection of a control unit (amphitheater/laboratory) that the user wishes to monitor in order to ensure optimum ambient conditions.

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Fig. 8.

Setting application functionality: a) setting temperature optimal limits, b) setting the temperature value to be controlled.

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Fig. 9.

Temperature and relative humidity after measuring.

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Fig. 10.

Light intensity and carbon dioxide (CO₂) concentration after measuring.

During measurements within the application, it is possible to choose which ambient parameters can be monitored. The display of the measured parameters is in the form of graphs, for each of the parameters separately. Also, it is possible for the user to provide a statistical overview of the measured values of the parameters.

The ambient parameters were measured with a prototype of a smart data logger for 9 days (from 13th of June to 22th of June, 2019). Measurement of ambient parameters was carried out at the amphitheater A3 at the Faculty of Electronic Engineering in Niš, Serbia. In the period when the measurement was carried out, preparatory classes and exams were held.

During the measurement period, the weather was mainly sunny and warm, as can be seen in Figs 9 and 10, respectively. The measurement began on Thursday (June 13th) at 2:00 pm, when the exam was over and when the students left the amphitheater. The value for the temperature was beyond the optimum values during the measurement (above the optimal range of 21°C to 23°C). The lowest temperature was measured on 21 June at 6 o’clock in the morning (T = 25°C), while the highest temperature value was measured on June 14 at 14 h (T = 29°C).

Relative air humidity ranged from 47% to 66%. Based on the results, it can be concluded that the values of relative air humidity periodically ranged from an optimal range of 65% to 80%.

The intensity of light during the examination, i.e. the preparatory classes, is periodically in optimal values (from 200 lx to 400 lx). After the completion of the exam, that is, the extinguishing of the light in the amphitheater, the intensity of the light has fallen sharply. The highest intensity value of light was measured during the exam (from 11 h to 15 h). Light intensity values ranged from 6 lx to 250 lx (in the period from 5 h to 19 h). During the weekend, the light intensity ranged from 9 lx to 140 lx, when there was no one in the amphitheater and no light was lit.

The concentration of carbon dioxide CO₂ reached the highest concentration in the period from 11h to 14h during working days, when exams were held and when the highest concentration of students was in the amphitheater. The CO₂ concentration ranged from 7% to 31%, where the lowest CO₂ concentration was recorded in early morning hours (around 5 h). As can be seen from the results, during the weekend when there were no students in the amphitheater, the concentration of CO₂ did not exceed 10%.

During the measurement, atmospheric pressure was monitored, the value of which ranged from 985 hPa to 996 hPa.

The mean values of the measured parameters can be monitored as indicated by using the application. The statistic overview of the measured values is possible at any time. Figure 11 shows the mean values of the ambient parameters after the measurement is completed. Also, in the same figure, the results of the measurement in the last 24 hours are given.

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Fig. 11.

Graphical and statistical presentation of the measured values.

By using the implemented system and control nodes, it is possible to control the ambient parameters using the application in order to keep the parameter values in the optimal range (Fig. 12).

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Fig. 12.

Temperature values controlled by the smart data logger.

As can be seen from Fig. 12, the temperature values were maintained in the optimal range. The results were obtained using the implemented system within 5 hours of measurement and control. It can be seen the switching points of the turn on the air conditioner in case the temperature value exceeds the set optimum value. Similarly, the switch-off point of the turn off the air conditioner is visible when the ambient temperature value is below the set optimum value. In relation to the reference papers in Section 2 (Theoretical background), where published papers from reference journals are listed, results obtained from the implementation of the described systems are not clearly indicated. Given that no manuscript to our knowledge has the ability to respond to the system based on measured data, we believe that our system has met the above goals.

This paper describes a reconfigurable smart data logger as part of smart faculty. The presented system is autonomous, which means that it monitors the ambient parameters itself and in accordance with the requirements of the user controls the environment in which it is located. The smart data logger system shown in this manuscript provides an opportunity monitoring, measurement, collection and control of ambient parameters in order to achieve optimum working conditions.

In addition to the main control of the unit that monitors the ambient parameters, control nodes are activated that control ambient parameters such as ventilation, lighting, windows blind, etc. Monitoring the measurement results is possible using the implemented smartphone application. With this application, it is possible to control all the parameters in the measuring room, as well as more data logger systems in particular.

The MQTT (Machine to Machine (M2M)/Internet of Things) protocol was used as the main communication protocol for greater data security. Compared to similar systems published in reference journals, this system has some advantages in terms of implementation. One of the advantages is that it is manufacturer-independent, so it enables integration with other smart faculty services or e-education.

The implemented system was used for monitoring and control of ambient parameters in the amphitheater during the exam and the preparatory classes at the faculty. An additional benefit of using this system is that the system independently controlled the ambient parameters when needed and provided optimal conditions for students and professors in the amphitheater. Unlike other rooms where the system was not applicable, professors and faculty were notified of required interventions (need to open windows, turn on/off air conditioners, etc.).

Also, the implemented system does not use the free commercial Cloud storage platform, as is the case in some of the papers published in reference journals. The manuscript also provides measurement results when the system is active and controls the environment according to user requirements, thus confirming the functionality of the system (monitoring, measuring and controlling the ambient temperature). Similar can be realized for other parameters being monitored. The disadvantages of this system are unreliable cheap sensors.