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The requirement for an efficient method for noise-robust detection of Dual-tone Multi-frequency (DTMF) signals keeping in mind the continuous evolution of telecommunication equipment is conspicuous. A machine learning based approach has been proposed in this research article to detect DTMF tones under the influence of various noises and frequency variations by employing the K-Nearest Neighbor (KNN) Algorithm. In order to meet accurate classification/detection requirements for various real-world requirements, a total of four KNN models have been created and compared, and the best one proposed for real-time deployment. Two datasets have been amassed, a clean dataset without noise and a noisy augmented dataset with perturbations that are observed in telecommunication channels such as additive white gaussian noise (AWGN), amplitude attenuation, time shift/stretch etc. Mel-Frequency Cepstral Coefficients (MFCC) and Goertzel’s Algorithm (used to estimate the absolute Discrete Fourier Transform (DFT) values for the fundamental DTMF frequencies) are employed to calculate features to be fed to the KNN models. The four models differ in being trained with and without the augmented data using the two aforementioned feature extraction algorithms, namely MFCCs calculation and the Goertzel’s algorithm. The proposed models have been verified and validated with unseen noisy testing data and it was found that the proposed KNN model D outperformed all the other models with a macro recall, precision and F1 classification score of 97.7, 97.70625 and 97.70046 respectively. The proposed model is also computationally inexpensive and showcases relatively low computing time and complexity.

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.

Obtaining information is one of the most important requirements for intelligence works, spy surveillance cameras and listening devices are among the important means for this. One problem of using these means is a mechanism of controlling them to sustain their work efficiently for the perpetuating of achieving the purpose of their installation. In this research, the problem of controlling these devices has been overcome, by designing a system dependent on the dual tone multi frequency (DTMF) and global system for mobile (GSM) networks. In the proposed work, designing and implementing a system to remotely and wirelessly control of the movement of spy cameras in all directions as well as the ability to control the on/off listing audio device anytime and anywhere. The proposed mechanism is implemented by dividing the work into nine modes, with each one performing one specific function. These work modes are used to control all system activities such as control the horizontal directional motor (HDM) to change the spy camera in different horizontal directions, control the vertical directional motor (VDM) to change the camera in vertical directions and control the working status of the listening device.

Smart Home Systems have achieved great interest in the recent years to make people’s life easier and more comfortable. Smart home system offers people to control home environment in efficient and comfortable manner. Technological advancement in recent years resulted in producing a large number of smart and sophisticated systems which promoted smart living technology. This paper presents complete analysis of various smart and intelligent home automation systems. Comparative analysis of existing smart home system has been made which provides a clear idea of the pros and cons of the existing systems. Working principle of different types of smart home systems such as Dual Tone Multi Frequency based, Global System for Mobile based, voice recognition based, Zigbee based, Bluetooth based, Internet and Wi-fi based, and Gesture based smart home systems has been studied. Comments according to different aspects and features have been made for the studied smart home systems which enable users to select suitable technology according to budget and needs.

This paper is concerned with the improvement of the Dual Tone Multi Frequency (DTMF) identification where the signals were transmitted via real communication channels. The frequencies of the DTMF signals are tracked using particle filtering method, a method that rely on the numerical computation in approximating the posterior probability density function (PDF) of the underlying state parameters, to identify which pad was pressed at the transmitter end. We propose and implement the adaptive resampling to improve the performance of the DTMF identification. The method enhances the quality of resampling stage generating a better set of particles which will be used for posterior PDF of the tones of the DTMF signals. Results reveal the advantage of using the proposed method in comparison to the conventional resampling scheme.

In this study, we investigate the design and simulation of an electronic system for remote controlling the level of light intensity of an electrical lighting system used for a certain desired application. The remote controlling is done using the keypad of any Dual Tone Multi Frequency (DTMF) based telephone handset. A DTMF tone command sent from a transmitting fixed or mobile phone terminal will be used to activate a system of relays that control the required level of light intensity. An appropriate active bandpass filters are designed for recognition of the DTMF tones of the transmitted digit. The bandpass filters and the additional subsequent stages of the overall electronic system are simulated and tested using MULTISM. Light intensity controlling is useful to avoid unnecessary electrical power wastage and the remote controlling eliminates the physical presence of a person for adjusting the required level of lighting at the desired location.

This technical paper aims at bringing about a huge development in this domestic and agriculture sectors to protect the farmer's interest thereby ensuring the overall growth of this country's economy. The topic is all about introducing a toll-free automation system for farmers who are considered to be the lifeline of India. Automation plays an important role in every field of work and segment of human life in helping the human beings to improve their functioning. Dual-Tone Multi-Frequencies has numerous applications and utilization in a broader perspective. The usage of DTMF touch tones by customer service has increasingly gained its importance and attention in the field of automation albeit it is not free of cost. Considering the poor economical background and condition of majority of Indian farmers, the automation system should be so designed to save their money in a cost effective manner as a onetime investment device. To put it in a nutshell the technicality involved in this project is that DTMF beep ringtone is set as a ringtone in a mobile phone rather than its being used in any distant automation system. The function of DTMF Decoder is to decode DTMF tone in binary numbers that would be received through a missed call. Thus the code generated in the previous step activates the microcontroller that would trigger the relays to operate appropriate appliance that was intended. The whole aim of this project is to design and install a high secured distant controlled toll-free automation system that would empower the farmers to take care of the entire needs in one stroke in their day-to-day agriculture activity.

Introduces a system design scheme of the telephone dialer based on Arduino, including the design principle, hardware and software design and the experimental results in this paper. The scheme is based on the dual tone multi frequency (DTMF) dialing mode, using the Arduino UNO as the main controller, the serial port send out the telephone number to be dialed, speaker synthesize the voice.

The paper represents a smart gadget to avert the calamitous effects of pest bugs in the farming land as well as in household commodities. In this paper, development and performance analysis of smart ultrasonic insects repellent device has been demonstrated. This device is able to generate different types of frequencies which are very helpful to repel different types of insects. It can be controlled from any distance with DTMF (Dual Tone Multi Frequency) technology. Besides, manual control with night mode via LDR (Light Dependent Resistor) has also been employed. The device would be charged through solar energy system which is a cost effective approach. A power amplifier along with a microcontroller known as Arduino Uno as well as solar charger circuit regulator and solar panel are used. The implementation of this device in farmland has shown a great reduction of bugs attack compared to the other land which doesn't have one.

Interactive Voice Response System (IVRS) is an automated system which is multi-lingual and makes use of text-to-speech (TTS) technology. This paper describes the implementation of an Interactive Voice Response System personalized especially for students to obtain any information desired by them in a reliable and timely manner by just placing a normal call, thus being a building block of a smart city. It works on a 24/7 basis and is very user friendly. The IVRS system comprises of ring detector hardware, dual tone multi frequency decoder (DTMFD), microcontroller, serial interface unit, computer and cell phone. It includes a ring detector hardware which identifies the caller and connects the identified caller to a computer. When a caller presses a key from their cell phone the input is produced in the form of dual tone multi frequency signal. The computer generates voice response dynamically based on the key pressed by the caller. A "Text to Speech Converter" converts the database into a voice format as per the response given by the caller.

Home automation or known as smart home is a home which is equipped by a system for controlling and integrating electronic devices, such as lighting, home theather, CCTV (closed-circuit television), HVAC (heating, ventilation, and air conditioning), motion sensor, security lock sensor for gates or doors, and etc. Its main purpose is to provide the improved simplicity, energy efficiency, higher security, and better feelings at home for the user benefits. Smart phone could be integrated as part of ring tone sensor for security door lock automation system. Therefore in this work, locking automation system using smart phone polyphonic tone sensor has been designed and implemented. A simple unlocking mechanism is explained as follows. The DTMF (Dual Tone Multi Frequency) module which has simply been programmed with Arduino was used to receive the polyphonic tone signal which is embedded in smart phone system. Then that signal will be processed by Arduino Uno, so the solenoid will automatically unlock the door. But, after three seconds delay, it will lock again (protection system). However, this system still has some drawbacks, such as low security system, short working-range of sensitivity, and limited amount of password digits. Moreover, those limitations could be improved/solved in the near future.

In the design, the MCU AT89C52 is the core of the system. The system can send and receive the DTMF signal, which can identify the city telephone number or the long-distance telephone number. According the number, it can billing and show call duration and call cost. It can realize automatically the conversion between the full price and the discount price. It can billing accurately and conveniently query ticket information. It is configurable product and resets rate by pressing a button. It is low cost and low power consumption.

Interactive Voice Response (IVR) Systems have been developed by enterprises to provide better services to the customers by allowing an automated machine to interact with humans through the use of voice or Dual Tone Multi Frequency (DTMF) keypad tones. But the IVR systems being developed today do not provide ease of use to the customers as they are monotonous. The present IVR systems lack dynamism, have very less degree of failure recovery and use APIs that are system dependent. In this paper we are proposing an Intelligent Interactive Voice Response System (IIVR) that generates a context-based dialogue using semantic web service composition and Expert System. This approach provides quality service to the customer by reducing the conversation time and by providing maximum information needed by the user. We use Java Expert System Shell (JESS) Rule Engine for generating the dialogue based on the context and thus optimizing the request-reply dialogue process between the service provider and consumer of the IVR systems. Furthermore, we use Ontology-based knowledge representation and we extract the necessary information from the ontology using semantic web services to further refine the dialogue generated by the IVR system.