scholarly journals IoT platform based Smart Assistant for Surveillance

2021 ◽  
Vol 20 ◽  
pp. 176-181
Author(s):  
Debalina Banerjee ◽  
Akashjyoti Banik ◽  
Sanjib Kumar Singh ◽  
Kandarpa Kumar Sarma
Keyword(s):  
Low Cost ◽  
Recognition System ◽  
High Energy ◽  
Raspberry Pi ◽  
Audio Signals ◽  
Energy Materials ◽  
Time Data ◽  
Metal Detector ◽  
Virtual Interface ◽  
Robotic Vehicle

Surveillance operations designed to be carried out by a robotic vehicle for entry into an area of higher risks and perform hazardous tasks form the core of this work. The system is integrated with a robotic vehicle that is controlled through a virtual interface and well supported by live video streaming. Here, the motion detection sensor is used as a simple but powerful human presence detector and alarm trigger. Also, the design has a metal detector and gas detecting sensor that can provide precaution against potential landmines present in the operations area and presence of chemicals, high energy materials or poisonous gases on regular and event-based occurrence. The real-time data of the gas sensor is stored in the local machine and also uses a speech recognition system developed using Raspberry Pi microcomputer to detect audio signals. It generates routine alarms on special/unknown/ first time patterns of audio threats. The system is designed using low-cost components.

scholarly journals Pengendalian Kualitas Air untuk Tanaman Hidroponik Menggunakan Raspberry Pi dan Arduino Uno

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ryan Ganesha Calibra ◽  
Irfan Ardiansah ◽  
Nurpilihan Bafdal
Keyword(s):  
Water Quality ◽  
Growth And Development ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Raspberry Pi ◽  
Time Data ◽  
Soil Nutrition ◽  
Remote System ◽  
Total Dissolved Solid

Water quality is very important for plant’s growth and development. Some of the important part of the water qualities are TDS(Total Dissolved Solid), EC(Electrical Conductivity), pH(Acidity). Cultivation inside a greenhouse provides some benefits but also have some deficiency, such as lack of soil nutrition because most plants inside greenhouse uses non soil growing media. To overcome the deficiency, An automated and remote system is needed to ease the controlling of water quality and nutrition feeding to the plant. This study aims to create low-cost greenhouse water quality monitoring that automatically display the real time data on a website. This research is done by using an engineering design methods. This system can be integrated with auto-pot watering system . The result shows that the system can adjust the TDS and pH as programmed, which are TDS= 1000-1200, and pH =5.5-6.5(these are recommended needs for Tomato plant). The TDS sensor in this reseach have the limitation of reading 0~1500ppm.

scholarly journals Extending Smart Phone Based Techniques to Provide AI Flavored Interaction with DIY Robots, over Wi-Fi and LoRa interfaces

2019 ◽  
Vol 9 (3) ◽  
pp. 224 ◽  
Author(s):  
Dimitrios Loukatos ◽  
Konstantinos G. Arvanitis
Keyword(s):  
Credit Card ◽  
Learning Experience ◽  
Low Cost ◽  
Voice Recognition ◽  
Smart Phone ◽  
Learning Activity ◽  
Raspberry Pi ◽  
Programming Environments ◽  
Robotic Vehicle ◽  
Educational Applications

Inspired by the mobile phone market boost, several low cost credit card-sized computers have made the scene, able to support educational applications with artificial intelligence features, intended for students of various levels. This paper describes the learning experience and highlights the technologies used to improve the function of DIY robots. The paper also reports on the students’ perceptions of this experience. The students participating in this problem based learning activity, despite having a weak programming background and a confined time schedule, tried to find efficient ways to improve the DIY robotic vehicle construction and better interact with it. Scenario cases under investigation, mainly via smart phones or tablets, involved from touch button to gesture and voice recognition methods exploiting modern AI techniques. The robotic platform used generic hardware, namely arduino and raspberry pi units, and incorporated basic automatic control functionality. Several programming environments, from MIT app inventor to C and python, were used. Apart from cloud based methods to tackle the voice recognition issues, locally running software alternatives were assessed to provide better autonomy. Typically, scenarios were performed through Wi-Fi interfaces, while the whole functionality was extended by using LoRa interfaces, to improve the robot’s controlling distance. Through experimentation, students were able to apply cutting edge technologies, to construct, integrate, evaluate and improve interaction with custom robotic vehicle solutions. The whole activity involved technologies similar to the ones making the scene in the modern agriculture era that students need to be familiar with, as future professionals.

scholarly journals Indoor Low Cost Assistive Device using 2D SLAM Based on LiDAR for Visually Impaired People

2019 ◽  
Vol 15 (2) ◽  
pp. 115-121
Author(s):  
Heba Hakim ◽  
Ali Marhoon
Keyword(s):  
Visually Impaired ◽  
Speech Synthesis ◽  
Low Cost ◽  
Optimal Path ◽  
Recognition System ◽  
Ultrasonic Sensor ◽  
Assistive Device ◽  
Raspberry Pi ◽  
Planning Algorithm ◽  
Indoor Scenarios

Many assistive devices have been developed for visually impaired (VI) person in recent years which solve the problems that face VI person in his/her daily moving. Most of researches try to solve the obstacle avoidance or navigation problem, and others focus on assisting VI person to recognize the objects in his/her surrounding environment. However, a few of them integrate both navigation and recognition capabilities in their system. According to above needs, an assistive device is presented in this paper that achieves both capabilities to aid the VI person to (1) navigate safely from his/her current location (pose) to a desired destination in unknown environment, and (2) recognize his/her surrounding objects. The proposed system consists of the low cost sensors Neato XV-11 LiDAR, ultrasonic sensor, Raspberry pi camera (CameraPi), which are hold on a white cane. Hector SLAM based on 2D LiDAR is used to construct a 2D-map of unfamiliar environment. While A* path planning algorithm generates an optimal path on the given 2D hector map. Moreover, the temporary obstacles in front of VI person are detected by an ultrasonic sensor. The recognition system based on Convolution Neural Networks (CNN) technique is implemented in this work to predict object class besides enhance the navigation system. The interaction between the VI person and an assistive system is done by audio module (speech recognition and speech synthesis). The proposed system performance has been evaluated on various real-time experiments conducted in indoor scenarios, showing the efficiency of the proposed system.

scholarly journals DESIGN AND IMPLEMENT AN IoT CLOUD FOR FIELD SURVEY BASED ON COAP PROTOCOL

2021 ◽  
Vol 25 (Special) ◽  
pp. 1-181-1-188
Author(s):  
Hadeel H. Azeez ◽  
◽  
Mahmood Z. Abdullah ◽  
Keyword(s):  
Real Time ◽  
Smart Cities ◽  
Low Cost ◽  
Raspberry Pi ◽  
New Schools ◽  
Time Data ◽  
Elapsed Time ◽  
Secure Storage ◽  
Cloud Server ◽  
Secure Place

Urban planning for smart cities requires collecting big real-time data, specially geolocation data from GPS sensors to use in many services like finding the best location for new schools so this data must be stored in a secure place with low cost and because the storage services offered from different cloud providers like Google, Amazon Web Service, Azure, etc., is not free. For these reasons, this study proposed Internet of Things (IoT) cloud architecture using Raspberry Pi model B+ as a cloud server with MySQL database services to provide free and secure storage at a low cost. The main contributions of this study lie in the Constrained Application Protocol (CoAP) server hosted in raspberry Pi to offer services in the proposed architecture of the IoT cloud with different scenarios to know the proposed architecture's ability for handling many user requests per second in terms of standard division, average elapsed time, error rate, throughput, and a number of real stored data in the database. AS a result, the proposed architecture handled 150 requests per second in real-time with an elapsed time of 1186 milliseconds without any error or data loss.

scholarly journals A Low-Cost Monitoring Platform and Visual Interface to Analyse Thermal Comfort in Smart Building Applications Using a Citizen–Scientist Strategy

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 564
Author(s):  
Giacomo Chiesa ◽  
Andrea Avignone ◽  
Tommaso Carluccio
Keyword(s):  
Thermal Comfort ◽  
Low Cost ◽  
General System ◽  
Raspberry Pi ◽  
Time Data ◽  
Smart Building ◽  
Graphical Interfaces ◽  
Building Culture ◽  
User Friendly ◽  
Current Energy

Smart building issues are critical for current energy and comfort managing aspects in built environments. Nevertheless, the diffusion of smart monitoring solutions via user-friendly graphical interfaces is still an ongoing issue subject to the need to diffuse a smart building culture and a low-cost series of solutions. This paper proposes a new low-cost IoT sensor network, exploiting Raspberry Pi and Arduino platforms, for collecting real-time data and evaluating specific thermal comfort indicators (PMV and PPD). The overall architecture was accordingly designed, including the hardware setup, the back-end and the Android user interface. Eventually, three distinct prototyping platforms were deployed for initial testing of the general system, and we analysed the obtained results for different building typologies and seasonal periods, based on collected data and users’ preferences. This work is part of a large educational and citizen science activity.

scholarly journals Steering a Robotic Wheelchair Based on Voice Recognition System Using Convolutional Neural Networks

Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 168
Author(s):  
Mohsen Bakouri ◽  
Mohammed Alsehaimi ◽  
Husham Farouk Ismail ◽  
Khaled Alshareef ◽  
Ali Ganoun ◽  
...  
Keyword(s):  
Performance Test ◽  
Low Cost ◽  
Voice Recognition ◽  
Recognition System ◽  
Mobile App ◽  
Raspberry Pi ◽  
Speech Corpus ◽  
Dc Motor Drives ◽  
Software And Hardware ◽  
Robotic Wheelchair

Many wheelchair people depend on others to control the movement of their wheelchairs, which significantly influences their independence and quality of life. Smart wheelchairs offer a degree of self-dependence and freedom to drive their own vehicles. In this work, we designed and implemented a low-cost software and hardware method to steer a robotic wheelchair. Moreover, from our method, we developed our own Android mobile app based on Flutter software. A convolutional neural network (CNN)-based network-in-network (NIN) structure approach integrated with a voice recognition model was also developed and configured to build the mobile app. The technique was also implemented and configured using an offline Wi-Fi network hotspot between software and hardware components. Five voice commands (yes, no, left, right, and stop) guided and controlled the wheelchair through the Raspberry Pi and DC motor drives. The overall system was evaluated based on a trained and validated English speech corpus by Arabic native speakers for isolated words to assess the performance of the Android OS application. The maneuverability performance of indoor and outdoor navigation was also evaluated in terms of accuracy. The results indicated a degree of accuracy of approximately 87.2% of the accurate prediction of some of the five voice commands. Additionally, in the real-time performance test, the root-mean-square deviation (RMSD) values between the planned and actual nodes for indoor/outdoor maneuvering were 1.721 × 10−5 and 1.743 × 10−5, respectively.

Janus – A New Approach to Air Combat Pilot Training

2019 ◽  
Vol 2019 (4) ◽  
pp. 7-22
Author(s):  
Georges Bridel ◽  
Zdobyslaw Goraj ◽  
Lukasz Kiszkowiak ◽  
Jean-Georges Brévot ◽  
Jean-Pierre Devaux ◽  
...  
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
High Energy ◽  
Training System ◽  
Embedded Sensors ◽  
Pilot Training ◽  
New Approach ◽  
Combat Aircraft ◽  
Air Combat ◽  
The Cost

Abstract Advanced jet training still relies on old concepts and solutions that are no longer efficient when considering the current and forthcoming changes in air combat. The cost of those old solutions to develop and maintain combat pilot skills are important, adding even more constraints to the training limitations. The requirement of having a trainer aircraft able to perform also light combat aircraft operational mission is adding unnecessary complexity and cost without any real operational advantages to air combat mission training. Thanks to emerging technologies, the JANUS project will study the feasibility of a brand-new concept of agile manoeuvrable training aircraft and an integrated training system, able to provide a live, virtual and constructive environment. The JANUS concept is based on a lightweight, low-cost, high energy aircraft associated to a ground based Integrated Training System providing simulated and emulated signals, simulated and real opponents, combined with real-time feedback on pilot’s physiological characteristics: traditionally embedded sensors are replaced with emulated signals, simulated opponents are proposed to the pilot, enabling out of sight engagement. JANUS is also providing new cost effective and more realistic solutions for “Red air aircraft” missions, organised in so-called “Aggressor Squadrons”.

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