Dual-tone Multi-frequency Signaling Research Articles

Remote Vehicle Control through Cell Phone Using DTMF

Abstract: The aim of the proposed project is to use a mobile phone to drive a car. The project necessitates the use of two mobile phones, one to control the robot and the other to deliver DTMF signals to the robot vehicle. The commands are received by a DTMF decoder connected to an 8051 microcontroller, which then controls the vehicle movement with the help of a motor driver. Thus, with the motor driver IC, two DC motors enable vehicle movement based on commands supplied from the phone. The power source is a battery. New technologies can be implemented using a robotic vehicle. The Dual Tone Multi Frequency (DTMF) system is utilised to control the robot. In everyday life, DTMF technology can be valuable. To this generation, DTMF technology is unrivalled. The science of Digital Signal Processing underpins DTMF technology. Previously, a Radio Frequency circuit was employed for wireless control, but it had a significant disadvantage in terms of range. As a result, it restricts control and has a negative impact on the vehicle's performance. DTMF, on the other hand, transforms this deprivation of the Radio Frequency circuit into domination. It gives you a wider range of options for working and produces better results. The phone in the microcontroller is used to operate and maintain this system. The remote handling operation of a robot using Dual Tone Multi Frequency is referred to as wireless communication. Keywords: Dual Tone Multi Frequency, Voltage Regulator, Microcontroller, Cell phone, Motor Driver, DC Motor

Kendali Radio Repeater Komunikasi Dua Meter Band Menggunakan Sistem Telekontrol Dual Tone Multi-Frequency

Repeater strongly supports the use of radio communication equipment for communication. The location of the repeater is usually at a high altitude so that the repeater's radio wave beam is not blocked by anything. The repeater arrangement is done by going directly to the repeater location so it is very inefficient from the time and accommodation factor. Therefore, a study was conducted to control the radio repeater settings remotely in order to reduce the accommodation of repeater control by visiting the radio repeater location. Control of radio repeater settings uses DTMF (Dual Tone Multi-Frequency) technology which sends DTMF signals and then converts them to binary data to be processed into data that is used for repeater control such as turning on and off the radio, setting high and low power, and adjusting channels on the repeater. the radio repeater. This system is also equipped with sending notifications in the form of SMS of the repeater operational conditions or settings. The research resulted in a remote control system based on DTMF technology equipped with a GSM/GPRS SIM800L module which is used to connect a smartphone to the system and send repeater operational notifications after controlling the repeater setting function. By using Telkomsel provider, the resulting delay when sending orders is 0.5 seconds and the delay in receiving SMS notifications is 12.96 seconds. Meanwhile, using Indosat provider, the resulting delay when sending commands is 0.43 seconds and the delay in receiving SMS notifications is 10.57 seconds.

Robust dual-tone multi-frequency tone detection using k-nearest neighbour classifier for a noisy environment

Purpose Due to the continuous and rapid evolution of telecommunication equipment, the demand for more efficient and noise-robust detection of dual-tone multi-frequency (DTMF) signals is most significant. Design/methodology/approach A novel machine learning-based approach to detect DTMF tones affected by noise, frequency and time variations by employing the k-nearest neighbour (KNN) algorithm is proposed. The features required for training the proposed KNN classifier are extracted using Goertzel's algorithm that estimates the absolute discrete Fourier transform (DFT) coefficient values for the fundamental DTMF frequencies with or without considering their second harmonic frequencies. The proposed KNN classifier model is configured in four different manners which differ in being trained with or without augmented data, as well as, with or without the inclusion of second harmonic frequency DFT coefficient values as features. Findings It is found that the model which is trained using the augmented data set and additionally includes the absolute DFT values of the second harmonic frequency values for the eight fundamental DTMF frequencies as the features, achieved the best performance with a macro classification F1 score of 0.980835, a five-fold stratified cross-validation accuracy of 98.47% and test data set detection accuracy of 98.1053%. Originality/value The generated DTMF signal has been classified and detected using the proposed KNN classifier which utilizes the DFT coefficient along with second harmonic frequencies for better classification. Additionally, the proposed KNN classifier has been compared with existing models to ascertain its superiority and proclaim its state-of-the-art performance.

Deep back propagation–long short-term memory network based upper-limb sEMG signal classification for automated rehabilitation

Autonomous rehabilitation training for assisted patients with injured upper-limbs promotes the regenerative communication between muscle signals and brain consciousness. Surface electromyographic (sEMG) is a type of electrical signals of neuromuscular activity recorded by electrodes on the surface of the human body, which is widely applied for detecting gestures and stimuli reactions. Experimental results proved the importance of the sEMG signals for extracting such reactions, in which, the segmentation and classification of the sEMG are vital tasks. The objective of the present work is to segment and classify the sEMG signals of patients to assist the design of clinical rehabilitation devices based on the classification of sEMG signals. In the pre-processing stage, a dual-tone multi-frequency signaling is designed for signal coding; subsequently, the pre-processed sEMG signal is transformed by the Fast Fourier Transfer. Afterward, a time-series frequency analysis is performed by applying Hidden Markov Models. A basic traditional long short-term memory (LSTM) model is addressed for waveform-based classification to be compared to the proposed improved deep BP (back-propagation)–LSTM for sEMG signal classification. Seventeen performance features are selected for evaluating the proposed multi-classification, deep learning model for classifying six actions, namely moving gesture of grip, slowly moving, flexor, straight lift, stretch, and up-high lift; which were proposed by rehabilitation physician. The experiment results indicated the superiority of the proposed method compared to other well-known classifiers, such as the neural network, support vector machine, decision trees, Bayes inference, and recurrent neural network. The proposed deep BP–LSTM network achieved 92% accuracy, 89% specificity, 91% precision, and 96% F1-score, in the multi-classification of the sEMG signals.

Wireless Remote Controlled for Multi-station Irrigation

This paper presents the development of a wireless remote-controlled system with dual-tone multi-frequency (DTMF) signaling transmitter using android application system for multi-station irrigation and fertilizer dispersion. Fertigation are combination of two words which are fertilizer and irrigation. To be more precise, fertigation is the process of applying fertilizer through an automatic irrigation system. Plants need enough both of nutrients and water supply in order to grow up and produce a high market value crop. Inaccurate amounts of water and fertilizer can lead to unhealthy plants growth and the worst is, the plants will be dead. Although there are the timer-based fertigation systems, the system cannot control the exact amount of fertilizer and water needed by the plants as they operate by supplying same amount of water and fertilizer in a specific time set without considering the weather and soil condition. The android application system allows users to send commands from their smart phones to control various type of appliances such as lighting, watering, timer or even fertilizer. The system is equipped with Arduino Uno and relay drivers circuit for controlling the system appliances. The system is suitable for long range control applications which mean can be control by any device that using dual-tone multi-frequency signaling transmitter from anywhere in the world.

Processor PIC18F46K22 Applied as DTMF Generator

Submitted article describes an application of microcontroller PIC18F46K22 for generating DTMF (Dual Tone Multi-Frequency) signal. Used microcontroller is optimal for this application - it has timers with compare facilities, sufficient number of PWMs, powerful instruction set (extended - in comparison to classic PIC16xxx microcontrollers), etc. problematic of article relates to more branches - electronics, filters, signal generators, microcontrollers, telecommunications, programming. An important purpose was to create an experimental platform based on powerful microcontroller enabling implementation additional functions. There are together three different solutions of DTMF generating are described in article, they are compared as to the demands on external hardware and machine time of microcontroller. The first solution is based on sinus table, truncated onto 32 values. This solution uses 8-bit PORTD for value intended to external D/A converter. The second one solution exploits compare facilities of PIC18F46K22, only two pins of microcontroller are needed for described application. And the third solution is similar to the second, difference consists in exploiting of PWM microcontroller hardware. Presented solutions were created in context of works on dotation program Support of Science and Research in Moravia-Silesia Region.

Pitch perception and frequency-following response in inharmonic signals.

It has been suggested that auditory-evoked frequency-following response (FFR) is related to pitch [Greenberg et al., Hear. Res. 25, 91–114 (1987)], which is usually related to fundamental frequency of complex sounds. We examined FFR to dual-tone multi-frequency (DTMF) signals used in telephone communication. As these tones have been used to produce melodies, it was expected that they would have a measurable pitch and this was also determined in a behavioral task. Twelve subjects matched perceived pitch of DTMF signals to a pure tone via method of adjustment. In addition, the FFR to the same signals was recorded from the same subjects to establish whether significant FFR energy was present at the frequency of the perceived pitch. Correlation analysis of data from the behavioral task showed wide variation among subjects, with many identifying the perceived pitch as matching the lower of the two partials. Significant FFR energy was detected at both partials, which does not clarify the relationship between perceived pitch and the evoked response. In addition, we show that perceived pitch is highly context dependent and present data from FFR to stimuli in melodic contexts.

Processing dual tone multi-frequency signals for use with a natural language understanding system

A method for processing dual tone multi-frequency signals for use with a natural language understanding system can include several steps. The step of determining whether a audio input signal is a dual tone multi-frequency signal or a human speech signal can be included. If the audio input signal is determined to be a dual tone multi-frequency signal, the audio input signal can be converted to at least one text equivalent. Also, the step of providing the at least one text equivalent to a natural language understanding system can be included. The natural language understanding system can determine a meaning from the text equivalent.

Performance of dual tone multi-frequency signal decoding algorithm using the sub-band non-uniform discrete Fourier transform on the ADSP-2192 processor

Efficient decoding of Dual Tone Multi-Frequency (DTMF) signals can be achieved using the sub-band non-uniform discrete Fourier transform (SB-NDFT). In this paper, the details of its implementation on the ADSP-2192 processor are put forward. The decoder performance in terms of its computational complexity and computational speed of this algorithm, implemented on the ADSP-2192 processor, are compared for different implementations of the SB-NDFT algorithm, with and without optimization for the chosen DSP, ADSP-2912. The algorithm is tested for various types of input signals on the DSP and these are compared with the results from Matlab ®. Problems on using other DTMF decoding algorithms that use the conventional discrete Fourier transform (DFT) and the non-uniform discrete Fourier transform (NDFT) are also addressed.

The FCC's universal service rules (abstract)

The Telecommunications Act of 1996 is considered landmark legislation, especially in the area of universal service. However, the FCC performed even more groundbreaking activity. The FCC was given wide latitude by the Act to interpret the universal service provisions of the Act either narrowly or broadly; the FCC chose the latter. The FCC's interpretation of the Act will have a significant impact on the level of technology implementation and use in American classrooms and libraries. In March 1996, the FCC issued a Notice of Proposed Rulemaking (NPRM) on Universal Service. The NPRM also established a Federal-State Joint Board composed of three FCC Commissioners (the Chairman and two commissioners), four state public service commission representatives nominated by the National Association of Regulatory Utility Commissioners, and one utility consumer advocate nominated by the National Association of State Utility Consumer Advocates. On November 8, 1996, the Joint Board released its Recommended Decision and the FCC adopted its rules based on that recommendation in May 1997. The FCC ruled that all eligible schools and libraties should receive discounts of between 20 and 90 percent (depending on need) on all telecommunications services, Internet access, and internal connections, subject to a $2.25 billion annual cap. In addition, any funds not disbursed in a given year may be carried forward and disbursed in subsequent years without regard to the cap. This provision, according to the FCC, will provide schools and libraries with the maximum flexibility to purchase the services that will meet their communications needs most effectively. In a separate section of the rules, the FCC defined "core services" as: • Voice-grade access to the public switched network, with the ability to place and receive calls • Dual Tone Multifrequency signaling (touch-tone) or its functional equivalent • Single-party service • Access to emergency services • Access to operator services • Access to interexchange services • Access to directory assistance. • Support for toll limitation services (includes both toll blocking and toll control) for low-income consumers. However, as stated in the Act, the FCC was given the latitude to include additional services for schools and libraries. It could have chosen to provide schools and libraries with discounts on (1) only core telecommunications services; (2) core services plus some complement of additional services; or (3) all telecommunications services (including wireless). The FCC adopted the third option, that discounts be provided on all telecommunications services. It stated that this guideline would provide schools and libraries the maximum flexibility to purchase whatever package of telecommunications services they believe would meet their telecommunications service needs most effectively and efficiently. <i>Current Status:</i> The FCC ruled that it will permit schools to begin using discounted services on January 1, 1998. The presentation will discuss the current status of this legislation.

Artificial neural networks in measurements

This paper, after a brief theoretical background to Artificial Neural Networks (ANNs) reviews their utilization in the field of measurements. The criteria used for choosing between the possible ANN software and hardware implementations are then discussed. The advantages and disadvantages of the possible analogue or digital hardware implementation are also detailed. Some of the applications of ANNs in the measurements field, variously utilizing software, analogue or digital hardware implementations are shown. In particular, the strategies for building suitable ANN-based software models of mixed analogue/digital measurement devices are presented. Successively, a method for designing a neural network able to pre-process signals in an analogue mode is described. Finally, the architecture of a DSP-based neural apparatus for the real-time measurement of the components of a dual-tone multi-frequency signal is given.

Rapid DTMF signal classification via parallel cascadeidentification

The parallel cascade identification of nonlinear systems is used for the rapid recognition of dual tone multi-frequency (DTMF) signals, i.e. the ‘dual tones’ used to encode the digits on a telephone keypad. The authors demonstrate that parallel cascades can correctly identify DTMF signals with half or less than half of the input data required by current methods.

Characterization of low-rate digital voice coder performance with non-voice signals

This paper describes the test methodology employed for the performance evaluation of the CCITT 16 kbit/sLD-CELP coder (Recommendation G.728) with non-voice signals. This methodology is sufficiently general that it can be employed for the evaluation of other low transmission-rate digital speech coders. The types of non-voice signals considered in this paper include voiceband data, network signaling, circuit continuity tones and dual-tone multi-frequency signaling.

A robust approach to tele-control using DTMF signaling (telephone call transferring equipment)

A novel method is proposed which is effective in preventing malfunction in the DTMF (dual-tone multifrequency) signal decoder caused by the holding melody. When the monitoring time is one second, the probability of a malfunction is at most 0.01. The proposed approach is a double DTMF signal monitoring method using the statistical characteristics of a DTMF signal decoder for a holding melody. >

Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions

The problem of predictor mistracking for narrowband signals in backward adaptive ADPCM (adaptive digital pulse code modulation) speech coders is shown to arise as a result of feedback from the signal reconstruction filter to the predictor adaptation process. A class of residual-signal-driven lattice predictors (PR) is defined that guarantees tracking for all signals without regard to the order of prediction. The LR predictor enhances speech and DTMF (dual-tone multifrequency) signal transmission performance in the presence of transmission errors. Under error-free transmission conditions, a segmental SNR (signal-to-noise ratio) drop for speech of nearly 2 dB may be encountered for the LR predictor relative to the classical signal-drive lattice predictor. In most practical telecommunication applications, however, this degradation is outweighed by the improved robustness of the predictor. >

Telecommunications device for the hearing impaired

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