The software product is proposed for performing the dispatching task of distributing water A method for determining the location of out-of-state situations using the SDS-TWR method is proposed, which allows you to accurately establish the radius of their potential occurrence in the multimedia data store. A new informative parameter for measuring the distance between radio modules located in the multimedia data storage is presented, which is based on the control of the rotational parameters of the direct current electric motor. A new approach to distance measurement is used, which includes the procedure of converting the power of a radio signal into a PWM signal, which affects the speed of rotation of the shaft of an electric motor, which controls a special generator of the frequency of the light flux. Such a procedure allows not only to determine the distance between radio modules, but also to transmit information containing data on the penetration of multimedia data storage using optical communication. The presented technique opens up new prospects for determining the locations of occurrence of emergency situations related to the penetration of multimedia data storage, in the absence of a signal or its insufficient power for data transmission.
Wireless sensor networks are rapidly gaining popularity due to their versatility and wide range of applications. An important aspect of such networks is the ability to accurately determine the geographical position of their components, which is necessary for the effective operation of the system of monitoring and control of multimedia data storage. Therefore, there is a need to collect data related to various physical parameters of such components, such as movement, distance between them, temperature, signal strength, etc. For this, a variety of sensors are used that can measure and store important indicators. The number of objects in a sensor network can be significant, which provides ample opportunities for data analysis and management. However, the presence of a large number of objects in the network introduces its own difficulties, in particular, in determining the exact location of each of them. This requires high accuracy and reliability in positioning and navigation systems. Traditional methods such as Time of Arrival (ToA) and Time Difference of Arrival (TDoA), although effective, still have certain limitations, especially in terms of accuracy and reliability when used over long distances. In the context of the development of the Internet of Things (IoT) and wireless technologies, there is a need to develop new, more effective methods for determining the location of objects. One such method is Symmetric Double Sided Two Way Ranging (SDS-TWR), which offers to solve the problems associated with inaccuracies in determining the distance.
The SDS-TWR method opens up new opportunities for accurate determination of object coordinates, which is an important aspect in the deployment and management of modern wireless sensor networks. At the same time, scientists are trying to get an additional informative parameter for distance measurement, based on signal strength, but face the problem of the influence of the environment on the signal. This includes interference, such as reflection, absorption, and scattering of the signal, which can significantly distort the distance estimate. These factors can affect the reliability and accuracy of measurements, especially in challenging environments such as urban landscapes or densely populated industrial areas where multiple interferences and various noise sources are possible. Therefore, there is a need to create a new principle of transmitting information about the state of signal strength, or its absence in general.
Considering the various methods of estimating the distance between two nodes by measuring the signal propagation time, the most popular ones should be highlighted. One of the simplest methods is the use of Time of Arrival (ToA), where the distance is determined in direct proportion to the time required for a signal to travel from one node to another. This method requires precise synchronization between nodes.
Another method, Time Difference of Arrival (TDoA), is based on determining the difference in the time of arrival of a signal from one node to several other nodes, or between several signals that arrive from one node to another. This method is widely used in cellular communication and requires synchronization of receiving nodes. Also, this method often requires additional equipment to transmit different types of signals, such as radio and ultrasound signals. Ultrasonic techniques used in conjunction with radio signals can provide measurements accurate to within a few centimeters. However, these methods have limitations, such as high cost, which is associated with the need to use additional equipment. In addition, there are limitations associated with the range of the ultrasound signal. Studies that have been conducted to evaluate bit errors (BER) and signal-to-noise ratio (SNR) with changes in noise power and data rate have shown that the level of signal power depends on many factors, the vast majority of which are caused by electromagnetic interference [1]. But taking into account the fact that when applying such methods it is difficult to obtain high accuracy, it is indicated in the work [2] that RSSI can be used to determine the location, if the error is 3-5 m.
A study based on the analysis of the paper [3] evaluated the effect of frame size on data delay in ZigBee system, especially when the RSSI value changes. This is quite important for delay-sensitive applications such as video data. The study helps to understand how changes in the frames transmitted by the ZigBee coordinator to the end nodes and vice versa affect the delay. It also expands on previous findings that distance between ZigBee modules affects signal strength by focusing on analyzing parameters that affect ZigBee communication indoors rather than outdoors. However, the problem of estimating RSSI without taking into account signal losses and additional interference also needs to be solved. This requires the search for new information parameters.
The article [4] presents a method for measuring distances between devices conforming to the IEEE 802.15.4 (ZigBee) standard, which uses a 2.45 GHz chip. The technique is based on the use of standard communication packages for simultaneous data transmission and localization. To increase the accuracy of positioning in difficult conditions, the method of coherent synthesis of measurements in different channels and estimation of the signal phase is applied, allowing the use of the full ISM bandwidth of 80 MHz. The experiments showed a positioning error of less than 16 cm and 9 cm with a standard deviation of less than 3 cm and 1 cm, respectively, demonstrating a significant improvement in accuracy compared to traditional methods. However, in the studies that were conducted, the influence of the dependence of radio interference, which can significantly change the characteristics of the obtained results, was not taken into account.
Thus, taking into account a number of features related to destabilizing factors, there is a need to create new ways of measuring the distance between radio modules based on additional informative parameters. In such conditions, it is important to consider the possibility of transmitting information in the absence of sufficient power of the radio transmitter.
In this paper, the method using ToA and the TDoA method are compared with the Symmetric Double Sided Two Way Ranging (SDS-TWR) method, which is proposed to solve the problem of increasing distance measurement error. At the same time, a new method of converting the power of the received radio signal into the mechanical moment of the electric motor is proposed to build a scale for visualizing the distance between the transmitter and the receiver of the radio signal. This will allow the construction of a distance measuring device to determine the location of an intrusion into a multimedia data store based on RSSI data.
There are a number of technologies that use different approaches to measuring distances using radio signals to determine the location of a transmission node. The most popular are the methods based on the determination of the power of the input signal (Receive Signal Strength Indication), time of signal passage (Time of Flight), phase shift of radio waves (Phase Difference) and determination of the angle to the object (Angular Positioning). Due to the structural difficulties in the organization of the last method and the relative high cost of the second-to-last method, methods based on determining the power of the received signal and calculating the signal transit time have become most widespread [5, 6].
The SDS-TWR technology utilizes a modification of the Time of Flight method named Symmetric Double Sided Two Way Ranging (SDSTWR). SDSTWR is an advancement of the Round Trip Time (RTT) method. To measure distances using RTT between objects A and B, object A sends a measurement request packet to object B and records the sending time. Upon receiving the packet from A, object B sends back an acknowledgment packet (ACK) to A. Object A, upon receiving the ACK packet, records its arrival time.
The RTT method employs hardware-generated ACK packets, assuming equal packet processing
time for both objects. The sending time of the measurement request packet and the receipt of the
ACK packet are also hardware-recorded. This setup allows for the predetermination of packet
processing time and the calculation of the signal propagation time ( ) using a specific formula [7]:
= − , (
2 where is the time measured by object A from the moment of sending a packet to object B until receiving an ACK packet from object B; is the time measured by entity B from receiving a packet from entity A to sending an ACK packet. Given the speed of signal propagation in the environment of a known and constant value, it is easy to calculate the distance between objects.
The accuracy of measuring time intervals, and therefore distances, is significantly affected by the frequency stability of crystals used in transceiver modules when using SDS-TWR technology. The degree of accuracy is characterized by the error value ppm (parts per million), for convenience, it is written in whole numbers. A value of 1 ppm corresponds to an error of 0.0001%, or 10–6. For example, for a crystal with a nominal frequency of 4 MHz and a frequency stability of 1 ppm, the maximum frequency deviation from the nominal will be 4000000 x 10–6 = 4 Hz.
Consider the effect of the ppm crystal on distance measurement. Suppose that the system consists of two objects, A and B, and their clocks run at the same speed.
Generally, packet distribution time is much shorter for TRTT and . The time , (s) usually does not exceed a few tens per second, and and are often about 1 ms or more = = .
4
When analyzing the expression, it can be seen that the difference between the values measured by one clock is included in each of the brackets. In particular, it should be noted that this formula is applicable if Treply A ~ Treply B, therefore, the greater the difference between these times, the greater the distance measurement error.
Thus, the SDSTWR method makes it possible to use less stable crystals, which fundamentally reduces the cost of the equipment used and at the same time ensures acceptable accuracy of distance determination. It is these important prerequisites that led to the emergence of promising SDS-TWR technology. In addition, it should be noted that since the fixation of the values of all times is carried out by the hardware part of the transceiver, the parameters and operating modes of the controlling microcontroller in no way affect the accuracy of determining the distances [6, 7]. However, it is important to preserve the integrity of the signal in conditions of individual interference. Thus, studies that have been conducted to evaluate bit error (BER) and signal-to-noise ratio (SNR) with changes in noise power and data rate have shown that the level of signal strength depends on many factors, the vast majority of which are caused by electromagnetic interference [8, 9]. !) + ( " −
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To conduct experimental research, distance measurement experiments were performed in wireless sensor networks using the Cisco Packet Tracer program. Let's create a network model using various devices connected by wireless channels. The main attention is paid to the interaction of the server and the network gateway. Experiments will include distance measurement using SDS-TWR radio modules and ATmega644 microcontrollers.
An analysis of emergency detection scenarios will be conducted and an automated data recording system will be used. Experiments will be conducted in an open area using different methods to confirm the accuracy of the measurements. The Cisco Packet Tracer program was launched and the necessary items were selected: motion detector, web camera, server and ZigBee home gateway in the device panel (Figure 1). The multimedia storage and the network gateway are connected by a wireless channel (FastEthernet0 and Ethernet1).
This model represents only a single segment of a distributed network, not the entire network, which consists of many segments of the same type and can extend over large distances depending on the area.
Found all the necessary elements for the construction of the model. This requires a smoke detector, a gate, a siren, a ZigBee home gateway, and a smartphone. The smoke sensor, siren, and gateway are connected to the gateway with a direct cable (fa0/1 - 01, fa0 - 0/3, fa0 - 0/2) (Figure 2).
All experiments used radio modules consisting of an SDS-TWR transceiver and an ATmega644 microcontroller (Figure 3). The microcontroller, which was proposed to be used inside the DCL 100 (Figure 1) and DCL 10 0/2 (Figure 2) devices, acted as the master on the SPI bus.
The calculation of the distance between devices is introduced to duplicate the functions of the intrusion prevention system, in case of failure of the camera, infrared motion sensor, or smoke sensor. If it is known that all devices are stationary and the position of the sensors does not change, and in some segments, in the absence of changes in other segments, there is an increase in the signal delivery time from the master device to the slave device, this may indicate an emergency situation (intrusion of foreign objects, fire, or smoke). It is known that the listed phenomena reduce the signal level. You should pay attention to this segment. Therefore, further research on the calculation of the distance between sensor network devices is useful from the point of view of localization of the radius of a possible emergency situation, in case of failure of other systems.
The Master module was connected to the Server-PT computer (Figure 1) through an RS232 interface (Figure 3) with a specially written program for automated recording of measurement results, which in most experiments were received once per second. Namely, experiment number, measurement number, current date and time, actual distance measured with a tape measure or laser rangefinder, as well as the result of distance measurement using SDS-TWR technology. The output power of the radio signal was 1 mW. The stationary radio module (Master) was most often fixed on a wooden stand 0.8 m high, and the mobile one (Slave) on a wooden pole 1.8 m long. Transceivers were equipped with standard antennas of the M04S type (1/2-wave dipole).
The experiment consisted in measuring the distance in an open space next to the road surface along an asphalt road. Both modules were fixed on poles at a height of 1.5 m from the road surface in the direct line of sight of each other. The stationary module (Master) was connected to the computer. The second module (Slave) was carried along the road by one of the experiment participants. In Figure 4 you can see the curves obtained by averaging the results of 10 measurements.
The horizontal axis shows the actual distance in meters and the vertical axis shows the difference between the SDS-TWR measured and the actual distance (also in meters): the measured distance is always greater than the actual distance due to the packet propagation technology used. The time may increase due to emergency situations. Situations where a false measurement point is supplemented by a 90% confidence interval for the mean value (Figure 5).
The first three curves were obtained on different days for one pair of modules (Master - 1, Slave - 2), on the remaining curves the Slave modules were changed.
In this way, it was possible to propose a model of the system for identifying emergency situations, which allows you to determine the radius of their possible occurrence in case of failure of the main systems. Based on the conducted experiments, the main conclusions can be drawn:
The applied radio modules of the SDS-TWR method allow quite accurate measurement of distances. In this case, the measurement results are slightly overestimated (depending on the external conditions), which may also indicate the occurrence of emergency situations.
Given that two main methods can be used to determine the distance: ToF (Time of Flight) and with the help of RSSI, to obtain an additional informative parameter, you can supplement the RSSI (Received Signal Strength Indicator) measurement procedure, which provides an estimate of the radio signal strength , which is received by the wireless device.
So, the built-in software of the device, built on the IEEE 802.15.4 (ZigBee) standard, measures the strength of the received signal. Signal strength is determined by the amplitude of the received signal and is expressed in decibels relative to milliwatts (dBm). The signal amplitude can be defined as the maximum deviation of the signal from its average value. The conversion of signal amplitude into decibels can be represented as follows [10–15]: + mW %&' = 10 ⋅ () * . , where P is the signal power in milliwatts.
But there is a certain drawback of this method: the accuracy depends on the distance. This method works perfectly only in an open area. Obstacles and reflective surfaces significantly reduce accuracy. However, this method is very easy to implement at the hardware level, problems will arise only when calculating the distance on the computing server. Therefore, it is recommended to use two methods at the same time to accurately measure distances.
At the hardware level, the process is relatively simple. The beacon periodically sends signals to the base station. The base station, in turn, records the device identifier, received signal strength (RSSI) and packet arrival time. The last parameter is critically important for tracking the object's route. The collected information is transferred to the server, where further analysis and calculations take place. But, if the hardware part of the system is relatively simple to implement, data processing and analysis on the server require more complex calculations.
According to the Fries signal transmission equation, we have the dependence of the distance
between radio modules on a number of known signal power parameters and antenna gain
coefficients [16–18]:
(
+ 45 where / is the distance between the transmitter and the receiver; +1 - signal power emitted by the transmitter; 2 3 - antenna gain of the transmitter; 2 3 - gain coefficient of the receiver antenna; + - received signal power; λ is the wavelength of the signal, which is calculated as , where c is the speed of light, and f is the frequency of the signal; 4π is a constant that reflects the spherical propagation of a wave in three-dimensional space.
The + parameter using a module that complies with the IEEE 802.15.4 (ZigBee) standard can be
obtained programmatically by connecting to it using a standard interface. Data processing is
implemented on the basis of a microcontroller, which processes the parameters received from the
network and calculates them using expression (
In this way, the transmission of received data can be carried out by a frequency method, using laser beams as a data transmission channel. To create frequency characteristics, the calculated distance indicator can be transformed into the electric power of a microelectric motor, which creates periodic pulses of the world flow, which are directed to a separate receiver (Figure 6). The frequency characteristics of such pulses can be obtained in a number of ways (a special receiver with photosensitive elements, a high-speed video camera, etc.).
The speed of rotation of the electric motor shaft can have a linear dependence on the R parameter,
if it is converted into the frequency characteristics of the world flow of the transmission channel.
For this, a PWM signal was generated at the output of the microcontroller to control the
commutating electric motor with a device such as the IRF740 field-effect transistor. In turn, this will
allow you to adjust the power of the electric motor depending on the width of the pulse that will be
generated by the microcontroller. In this way, measuring the distance between radio modules will
be provided with a new informative parameter, namely the frequency of rotation of the current
electric motor shaft, which can be removed by a wide range of means. So, the intensity of the received
signal (RSSI) is determined by receiving data from the radio module, then a control PWM signal is
formed in the microcontroller, which switches the power transistor to control the power of the
electric motor. The rotary motion of the electric motor disk generates the frequency characteristics
of the global beam, which is directed at the receiving device. Thus, we obtain a linear relationship
between the intensity of the received signal and the frequency characteristics of the light signal. In
Figure 7. the procedure is presented, which includes obtaining RSSI - 1, converting the PWM signal
level to control the power of the electric motor - 2, obtaining the frequency characteristics of the
light signal - 3, as well as the possibility of their transmission by generating an optical signal, the
frequency of which varies in proportion to the signal power [19–22]. This, in turn, allows to receive
a signal at long distances, regardless of radio interference. For this, you can use any frequency meter
or oscilloscope that can determine the frequency characteristics obtained by the optical receiver 4.
(
FgivJ ,
K =
A = , /E = /Q + />′ +
67ℎ8 1 /E MNOP
SA − S 2 ⋅ 5 ⋅ (F − 1)
R = SA , FgivJ = 6 ⋅ RFT *SA − 3 . , where: i – phase; t - current time; DA– voltage at the output of the constant voltage source; FgivJ - the current value of the average current task in phase i; MNOP- frequency of PWM modulation; A- PWM modulation period; Δ - the difference in the rise and fall times of the current during the PWM period; LΣ- total inductance of the load circuit of the autonomous inverter; /Σ- the total resistance of the load circuit of the autonomous inverter; /Q- Stator circuit resistance; />′- induced resistance of the rotor chain; K- electromagnetic time constant of the power supply chain; 67ℎ8 1- Short-circuit current of the power supply circuit; s - slippage of the asynchronous motor rotor; S - angular frequency of rotation of an asynchronous motor; SA- angular frequency of the signal that sets the current of the asynchronous motor. , 1 −
A
B,
At the same time, the use of an asynchronous electric motor to solve these problems will not be the best solution, since the need to convert constant voltage into an alternating one, providing a control system for an asynchronous electric motor will create certain difficulties.
Therefore, it is necessary to determine the dependence of RSSI on the frequency of rotation of the electric motor, which will allow obtaining the frequency characteristics of the output signal in proportion to the strength of the radio signal level received by the transmitter.
To modify the expression (
First, consider the standard dependence of shaft rotation speed on electrical parameters for a DC motor:
S = UV ⋅ (W⋅ Dmax − 6 ⋅ /), (
Then we modify (
UV ⋅ (W⋅ Dmax − 6 ⋅ /) = /> .
Thus, the use of an additional informative parameter will allow to increase the accuracy of
distance measurement by the RSSI method, since the signal transmission channel based on a laser
beam does not depend on radio interference, has almost no delay and does not require additional
calibration during operation. For example, two measurement methods were simulated, using (
As a result of the simulation, we can see that the signal after transmission by the optical method
is more stable, however, additional pulses are smoothed out due to inertia. Therefore, this method
requires additional research related to the selection of optimal parameters of the electric motor.
(
The SDS-TWR distance measurement error was found to be within 1–4 m and the random error of each measurement to be within ± 80 cm (90% confidence interval) and virtually independent of distance.
The use of an additional informative parameter significantly increases the accuracy of distance
measurement by the RSSI method. The peculiarity of this method is that the signal transmission
channel based on the laser beam does not depend on radio interference, has almost no delay and does
not require additional calibration during operation. In the simulation of two methods of
measurement, different conditions of signal reception were taken into account: in the first case (
Thus, the main advantage of using a laser channel for transmitting the frequency characteristics of the signal power is that it is possible to avoid the influence of external interference, which ensures more stable and reliable transmission of video data about the occurrence of an off-state situation in the multimedia data storage.
The author(s) have not employed any Generative AI tools.