scholarly journals Object Sorting Robot Mechanism on the Basis of Colour, Height and Type (Metal or Non-metal) using Human Voice Input

2019 ◽  
Vol 8 (2S4) ◽  
pp. 24-28
Keyword(s):  
Industrial Applications ◽  
Ultrasonic Sensor ◽  
Human Beings ◽  
Metal Detector ◽  
Voice Input ◽  
Human Voice ◽  
Intelligent Robots ◽  
Broad Term ◽  
Object Sorting ◽  
Sorting System

Automation is a very broad term which is basically used to handle different mechanisms and processes to reduce human efforts, time consumption and human energy. It reduces manual efforts, costs and is faster as well as more accurate than human beings. Sorting of objects is a very important aspect of agricultural machineries, food processing industries and various other industrial applications. Many kinds of intelligent robots are emerging these days. These systems collaborate with humans to accomplish tasks like sorting in an unstructured environment. Sorting plays a very significant role in the manufacturing and production industries. Also, sorting is one of the widely researched topics in today's time. This paper describes about a robotic mechanism for sorting objects. The Sorting system uses a TCS3200 Colour Sensor, an SR-04 Ultrasonic sensor, Metal detector, Bluetooth module and a Robotic push mechanism. Three different parameters like colour, height and type of object (metal or non-metal) is detected by setting the threshold and by giving the input one at a time by using human voice command via a Bluetooth module integrated with the Arduino. The three colours detected include red, blue and green. Also the range of distances or heights measured by the ultrasonic sensor reaches up to 200cmThe overall sorting is then carried out by the robotic mechanism

scholarly journals Automatic Pneumatic Power Based Object Sorting System by Using MITSUBISHI PLC

2015 ◽  
Vol 9 (1) ◽  
pp. 91-97
Author(s):  
P. Choudesh Varma ◽  
◽  
G. Venkateswarlu ◽  
Keyword(s):  
Object Sorting ◽  
Pneumatic Power ◽  
Sorting System

Self-Organized Map Based Learning System for Estimating the Specific Task by Simple Instructions

2013 ◽  
Vol 17 (3) ◽  
pp. 450-458 ◽  
Author(s):  
Hiroyuki Masuta ◽  
◽  
Yasuto Tamura ◽  
Hun-ok Lim
Keyword(s):  
Learning System ◽  
The Self ◽  
Service Robots ◽  
Specific Task ◽  
Human Beings ◽  
Simulation Experiments ◽  
Environmental Measurement ◽  
Intelligent Robots ◽  
Self Organized ◽  
Time Variations

This paper discusses a learning system for service robots to estimate specific tasks by using simple instructions from human beings. Intelligent robots are expected to operate in human living areas, so service robots should understand specific tasks from simple instructions given by human beings. It is important to perceive environmental situations and to adapt to human preferences. We propose a learningmethod using the Self-Organized Map (SOM) to estimate specific tasks from both human behavior measurement but also environmental measurement. Through simulation experiments, we verified that the proposed SOMbased method considers environmental situations associated time variations and show that service robots decide table-clearing tasks according to human intent.

Psychiatric Prolegomena: A Plea for the Help of Philosophy

Philosophy ◽  
1952 ◽  
Vol 27 (100) ◽  
pp. 39-50
Author(s):  
Harold Palmer
Keyword(s):  
Facial Expression ◽  
Personality Assessment ◽  
Human Beings ◽  
Human Voice

Personality may be defined as “that aspect of human beings where by we are recognized by others, ” that is, “that which constitutes recog-nizability.” The term therefore implies a subject-object field in which the object is another person or persons. There exist as many criteria of personality assessment as there are significant viewpoints of human beings, but there seems little doubt that the human voice is that which impresses us most about our fellows, closely followed by facial expression. Both these convey that whereby we assess “purpose” which is a most important matter about which we habitually assess others.

scholarly journals Starotestamentalne cuda w poemacie "Paschale carmen" Seduliusza

Vox Patrum ◽  
2014 ◽  
Vol 62 ◽  
pp. 331-356
Author(s):  
Tatiana Krynicka
Keyword(s):  
Common Sense ◽  
Laws Of Nature ◽  
Human Beings ◽  
Holy Trinity ◽  
Human Voice ◽  
History Of

Before turning to the wonderful Saviour’s deeds, that he strives to praise in Paschale Carmen, Sedulius introduces his reader into the old testamental history of salvation. In the Book 1, which fulfils the functions of a preface to the poem, he recounts 18 miracles that took place before Christ was born, since the ages of the Patriarchs to the period of the Babylonian captivity. These relations appear to be separate, self-contained stories. The longest is devoted to the miraculous fate of the prophet Elijah (lines 170-187); in the shortest the poet tells about the Balaam’s donkey, an animal without speech, who spoke to its master with a human voice (lines 160-162). Miracles fascinate Sedulius as extraordinary events, which deny the laws of nature and contradict common sense. At that they are sometimes con­nected with a marvelous metamorphosis. God performs miracles in order to show to the mankind His might, providence and kindness; to educate human beings and to prepare them for the coming of Christ; to foretell cosmic redemption at the end of times. Telling about the old testamental miracles Sedulius tends to refer both to the unbelievers and to the believers the revealed truth. He also aims to awake in the readers’ hearts wonderment, gratitude, love and trust towards the Holy Trinity.

scholarly journals Applicability of IoT in Solid Garbage Collection and Monitoring System for Smart Cities

2021 ◽  
Author(s):  
Dominic Abuga ◽  
Nallanthighal Raghava
Keyword(s):  
Garbage Collection ◽  
Smart Cities ◽  
Threshold Level ◽  
Ultrasonic Sensor ◽  
Raspberry Pi ◽  
Waterborne Diseases ◽  
Human Beings ◽  
Weight Measurement ◽  
Weight Sensor ◽  
Level Height

Abstract Waste management has been a challenge to many cities globally. Improper disposal of waste is harmful to human beings, flora, and fauna. In human beings, inappropriate waste disposal results in waterborne diseases such as typhoid and cholera, which are very dangerous. Waste collected and dumped in landfills produces methane gas which is more dangerous than carbon dioxide. Methane is a greenhouse gas, causes global warming, which has severe ramifications for our planet. In this paper, the applicability of IoT in solid garbage collection and monitoring framework for smart cities has been put forward. The proposed system is built using a Raspberry Pi Uno board that is interfaced with a weight sensor, ultrasonic sensor, and a GSM modem. The weight sensor will be placed at the bottom of the garbage bin for weight measurement. The Ultrasonic sensor will be affixed at the top of the garbage bin in order to measure the levels of waste. The Raspberry will have to be programmed in such a manner that when the garbage is almost being filled up, the other remaining level/height from the threshold level will be automatically displayed. When the solid waste in the garbage bin reaches the threshold weight, it will also set off the GSM modem, which will notify the person in charge of garbage collection. The personnel will send a message to the administrator in charge of garbage collection vehicles.

scholarly journals VOICE CONTROLLED VEHICLE USING MQTT SERVER

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
N Ayush Ubale ◽  
Pranavya M U ◽  
Poli Guha Neogi ◽  
Hardik Jethava
Keyword(s):  
Artificial Intelligence ◽  
Open Source ◽  
Mobile Application ◽  
Ultrasonic Sensor ◽  
Operating Costs ◽  
Android Application ◽  
Specific Location ◽  
Human Voice ◽  
Robotic Vehicle ◽  
The Voice

The voice-controlled vehicle was created to make human work easier, since we live in an artificial intelligence-driven world where robots perform many tasks. The human voice is used to drive the vehicle. A stable android mobile application built with android studio software transmits the speech. It's essentially a Wi-Fi link. Using the mobile application, we can operate the vehicle with our voice from anywhere. The NodeMCU IoT framework is free and open source. It includes firmware for the ESP8266 Wi-Fi module, a Espressif Systems SoC, and ESP-12 module hardware. With the application that has been created, human work may become simpler. Since the vehicle will be linked to Wi-Fi, we will be able to access it from any location in our project. He or she will use the Android application to send commands or voice commands such as forward, backward, left, right, left forward, left backward, right forward, right backward, and right forward, right backward. The pins have been connected to the NodeMCU esp8266, and the code to control the car has been written. When an object or vehicle inhibits the car's movement, an ultrasonic sensor is used to stop it. The voice is recognised and forwarded to the HiveMQ server, where it is processed. HiveMQ's MQTT broker is optimised for cloud native deployments to take advantage of cloud resources. The use of MQTT reduces the amount of bandwidth used to transport data across the network. Low overall operating costs are a result of efficient IoT solutions. The hivemq server receives the command from the Android application and sends it to the NodeMCU microcontroller, which programmes the code to drive the vehicle. The voicecontrolled robot vehicle project has military, surveillance, and human applications in scope. It's a voice-activated wireless robot vehicle. The project's main goal is to guide the robotic vehicle to a specific location. In addition, the project's main goal is to use voice to control the robot. It is now possible to have

scholarly journals Research on Multi-Object Sorting System Based on Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6238
Author(s):  
Hongyan Zhang ◽  
Huawei Liang ◽  
Tao Ni ◽  
Lingtao Huang ◽  
Jinsong Yang
Keyword(s):  
Deep Learning ◽  
Target Detection ◽  
Training Model ◽  
Normal Vector ◽  
Data Set ◽  
Integrated Network ◽  
Object Sorting ◽  
Sorting System ◽  
Rotating Target ◽  
Instance Segmentation

As a complex task, robot sorting has become a research hotspot. In order to enable robots to perform simple, efficient, stable and accurate sorting operations for stacked multi-objects in unstructured scenes, a robot multi-object sorting system is built in this paper. Firstly, the training model of rotating target detection is constructed, and the placement state of five common objects in unstructured scenes is collected as the training set for training. The trained model is used to obtain the position, rotation angle and category of the target object. Then, the instance segmentation model is constructed, and the same data set is made, and the instance segmentation network model is trained. Then, the optimized Mask R-CNN instance segmentation network is used to segment the object surface pixels, and the upper surface point cloud is extracted to calculate the normal vector. Then, the angle obtained by the normal vector of the upper surface and the rotation target detection network is fused with the normal vector to obtain the attitude of the object. At the same time, the grasping order is calculated according to the average depth of the surface. Finally, after the obtained object posture, category and grasping sequence are fused, the performance of the rotating target detection network, the instance segmentation network and the robot sorting system are tested on the established experimental platform. Based on this system, this paper carried out an experiment on the success rate of object capture in a single network and an integrated network. The experimental results show that the multi-object sorting system based on deep learning proposed in this paper can sort stacked objects efficiently, accurately and stably in unstructured scenes.

scholarly journals Review Paper on Microcontroller Based Object Sorting

2021 ◽  
Vol 9 (VII) ◽  
pp. 3287-3288
Author(s):  
Divya Balaso Kamble
Keyword(s):  
Frequency Analysis ◽  
Review Paper ◽  
Industrial Process ◽  
Experimental Results ◽  
Metal Detector ◽  
Dc Motors ◽  
Automatic Sorting ◽  
Manual Sorting ◽  
Conveyor Belts ◽  
Object Sorting

Sorting of products is a very difficult industrial process. Continuous manual sorting creates consistency issues. This paper describes a working prototype designed for automatic sorting of objects based on the metal detector KY-036 sensor was used to detect the colour of the product and the PIC16F628A microcontroller was used to control the overall process. The identification of the colour is based on the frequency analysis of the output of TCS230 sensor. One conveyor belts were used, it controlled by separate DC motors. The belt is for placing the product to be analysed by the colour sensor, having separated compartments, in order to separate the products. The experimental results promise that the prototype will fulfil the needs for higher production and precise quality in the field of automation.

Speech to Text Processing for Interactive Agent of Virtual Tour Navigation

2019 ◽  
Vol 1 (1) ◽  
pp. 31
Author(s):  
Dian Ahkam Sani ◽  
Muchammad Saifulloh
Keyword(s):  
Speech Recognition ◽  
Text Processing ◽  
Predictive Coding ◽  
Digital Signal ◽  
Recognition System ◽  
Human Interaction ◽  
Linear Predictive Coding ◽  
Voice Input ◽  
Human Voice ◽  
Backpropagation Method

The development of science and technology is one way to replace the method of human interaction with computers, one of which is to provide voice input. Conversion of sound into text form with the Backpropagation method can be understood and realized through feature extraction, including the use of Linear Predictive Coding (LPC). Linear Predictive Coding is one way to represent the signal in obtaining the features of each sound pattern. In brief, the way this speech recognition system worked was by inputting human voice through a microphone (analog signal) which then sampled with a sampling speed of 8000 Hz so that it became a digital signal with the assistance of sound card on the computer. The digital signal from the sample then entered the initial process using LPC, so that several LPC coefficients were obtained. The LPC outputs were then trained using the Backpropagation learning method. The results of the learning were classified with a word and stored in a database afterwards. The results of the test were in the form of an introduction program that able display the voice plots. the results of speech recognition with voice recognition percentage of respondents in the database iss 80% of the 100 data in the test in Real Time

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