Smartphone In Real Time Research Articles

Position and Temperature Detector for Autism Spectrum Disorder Children based on Sensor and Using IoT System

Children with Autism Spectrum Disorder (ASD) have characteristics where one cannot control emotions, which can cause tantrums that can impact behavior and body temperature. Based on this, they should be supervised by parents/relatives. To reduce the effects of these circumstances, this study seeks to design a technology system that can measure body temperature and detect the position of ASD children who can later monitor the activities they do. This system applies the ESP32 microcontroller and utilizes the GPS module to read the position of objects detected by the system and the MLX90614 temperature sensor, which can detect the body temperature of ASD children. Then, to facilitate checking, the control system is designed with an IoT system through the Blynk application to make it easier for users to supervise ASD children and can be accessed via smartphones in real time. In this study, detection testing was carried out on 3 ASD child subjects by grouping three conditions: namely, the child exits the location when the child is outside the predetermined location; then the child exits the body temperature when the child's body temperature is abnormal, and the child exits the location and body temperature outside normal. The results obtained show that the detector test results provide notifications to application users in the form of "child out of location," "child out of body temperature," and "child out of location and body temperature outside normal".

Position and Temperature Detector for Autism Spectrum Disorder Children based on Sensor and Using IoT System

Children with Autism Spectrum Disorder (ASD) have characteristics where one cannot control emotions, which can cause tantrums that can impact behavior and body temperature. Based on this, they should be supervised by parents/relatives. To reduce the effects of these circumstances, this study seeks to design a technology system that can measure body temperature and detect the position of ASD children who can later monitor the activities they do. This system applies the ESP32 microcontroller and utilizes the GPS module to read the position of objects detected by the system and the MLX90614 temperature sensor, which can detect the body temperature of ASD children. Then, to facilitate checking, the control system is designed with an IoT system through the Blynk application to make it easier for users to supervise ASD children and can be accessed via smartphones in real time. In this study, detection testing was carried out on 3 ASD child subjects by grouping three conditions: namely, the child exits the location when the child is outside the predetermined location; then the child exits the body temperature when the child's body temperature is abnormal, and the child exits the location and body temperature outside normal. The results obtained show that the detector test results provide notifications to application users in the form of "child out of location," "child out of body temperature," and "child out of location and body temperature outside normal".

RANCANG BANGUN SISTEM MONITORING DAN CONTROLLING SUHU COOL BOX VAKSIN MENINGITIS MPSV4 BERBASIS IoT

Meningitis is generally an infectious disease of the lining of the brain and spinal cord with manifestations of fever and stiff neck. Prevention efforts for meningitis include vaccination. Meningococcal polysaccharide vaccine (MPSV4) is a type of quadrivalent meningitis vaccine recommended to control meningitis outbreaks. In storage, this vaccine uses a cold chain and cool box with a temperature between 2-8˚C. For vaccination activities, the vaccine is stored in a cool box with a cool pack provided to maintain temperature stability in the cool box. A cool pack itself is a rectangular plastic container that is filled with water and then cooled in a refrigerator at a temperature of 2-8°C for a minimum of 24 hours. From the existing problems, the author had the idea to create an IoT-based MPSV4 Meningitis Vaccine Cool Box Temperature Monitoring and Controlling System Design. The working system of this tool, namely TEC, will maintain the cool box temperature according to needs. If the dht11 detects that the temperature is too high then both TECs will turn on, whereas if the temperature is stable then one of the TECs will turn off. The temperature inside the cool box will be displayed on the LCD and also sent via the NodeMCU ESP8266 to the Firebase database which will then be displayed on the smartphone in real time.

Wireless and Flexible Optoelectronic System for In Situ Monitoring of Vaginal pH Using a Bioresorbable Fluorescence Sensor

AbstractHerein, a miniaturized wireless sensing vaginal ring for the in situ continuous monitoring of vaginal pH and real‐time transmission of the pH data to a smartphone is reported, aimed at the diagnosis and management of bacterial vaginosis, a common condition frequently and adversely affecting women. The sensing vaginal ring consists of a bioresorbable pH fluorescence sensor placed on top of a polydimethylsiloxane ring encapsulating a miniaturized driving/readout optoelectronic circuit, data acquisition system, wireless transceiver, and power supply. The pH sensor consists of a micrometer‐thick porous silica scaffold conformably coated with a nanometer‐thick polymer multilayer stack and is intended to be replaced after 4 days. The sensor fully dissolves in biocompatible by‐products eliminating waste management issues; conversely, the ring embedding the circuit is reusable with new sensors. The pH sensor, as well as the sensing vaginal ring, show excellent performance in the continuous measurement of pH in vaginal fluid and can monitor the pH level over the physio‐pathological range of 3–7.5 with high linearity, accuracy, and reliability, transmitting the data to a smartphone in real time. The proposed technology can be immediately translated to other diseases, among which wound healing, intragastric activity, and cancer progression, where continuous monitoring of pH is required, as well as to other markers/analytes by engineering the polymer stack with suitable receptors, such as aptamers and other molecular probes.

Fully integrated wearable humidity sensor for respiration monitoring.

Respiration monitoring is a promising alternative to medical diagnosis of several diseases. However, current techniques of respiration monitoring often require expensive and cumbersome devices which greatly limit their medical applications. Here, we present a fully integrated wearable device consisting of a flexible LCP-copper interdigital electrode, a sensing layer and a wireless electrochemical analysis system. The developed humidity sensor exhibits a high sensitivity, a good repeatability and a rapid response/recover time. The long-term stability is over 30days at different relative humidity. By integrating the flexible humidity sensor with miniaturized electrochemical analysis system (0.8cm × 1.8cm), response current concerning respiration can be wirelessly transmitted to App-assisted smartphone in real time. Furthermore, the fabricated humidity sensor can realize skin moisture monitoring in a touch-less way. The large-scale production of miniaturized flexible sensor (4mm × 6mm) has significantly contributed to commercial deployment.

Design of Security System Device for Motorized Vehicles through the Telegram Messenger Application and Updating GPS Locations on Smartphones in Real Time with IoT-based Smart Vehicles

Currently, the number of cases of motorized vehicle theft is increasing. Lack of double security, when left by the owner, is one of the factors that cause vehicles to be easily stolen. Based on these problems, we designed a motorized vehicle security system device that can monitor the condition and update the vehicle location with a smartphone through Global Positioning System (GPS). Furthermore, it can send an active alarm in the form of a buzzer alarm when there is an indication of the danger of vehicle theft. Furthermore, send notifications to the user so that the user immediately locks the vehicle by controlling it remotely in real-time through the Internet of Things (IoT)-based Smart Vehicle Security System using the Telegram Messenger Application and Google Maps (GMaps). The results of testing the response time show that the best performance is very responsive at 2.776 seconds in monitoring and controlling the vehicle. Moreover, the results of testing the vehicle distance position with GMaps and GPS obtained the best performance with a success rate percentage of 97.35% and an error rate percentage of 2.65%. It aims to make vehicle owners feel safe and comfortable and prevent motorized vehicle theft.

On-Skin Flexible Pressure Sensor with High Sensitivity for Portable Pulse Monitoring.

Radial artery pulse pressure contains abundant cardiovascular physiological and pathological information, which plays an important role in clinical diagnosis of traditional Chinese medical science. However, many photoelectric sensors and pressure sensors will lose a large number of waveform features in monitoring pulse, which will make it difficult for doctors to precisely evaluate the patients’ health. In this letter, we proposed an on-skin flexible pressure sensor for monitoring radial artery pulse. The sensor consists of the MXene (Ti3C2Tx)-coated nonwoven fabrics (n-WFs) sensitive layer and laser-engraved interdigital copper electrodes. Benefiting from substantially increased conductive paths between fibers and electrodes during normal compression, the sensor obtains high sensitivity (3.187 kPa−1), fast response time (15 ms), low detection limit (11.1 Pa), and long-term durability (20,000 cycles). Furthermore, a flexible processing circuit was connected with the sensor mounted on wrist radial artery, achieving wirelessly precise monitoring of the pulse on smart phones in real time. Compared with the commercial flexible pressure sensor, our sensor successfully captures weak systolic peak precisely, showing its great clinical potential and commercial value.

Home Security and Fire Detection System Design Using IoT-based Microcontroller ATmega2560

A smart home security system or SmartHome is a new technology in this modern era with the concept of IoT (Internet of Thing), namely by utilizing internet connectivity by connecting a microcontroller device as a data processor for input and output with other components such as sensors that can communicate via smartphones. The PIR sensor and the MQ-2 smoke detector are one of the important components in a security system both at home and in buildings. Based on statistical data sources at the National Police Headquarters, crime in cases of theft is increasing and statistical data from https://www.jakartafire.net/statistics causes and occurrence of fires are still quite high. Based on the above problems, the author's motivation in making a home security system and fire preventive based IoT using microcontroller ATmega2560 Wi-Fi. This design prototype uses the ATmega2560 microcontroller component as input and output data processing, the HC-SR501 PIR sensor as a motion detection sensor, the MQ-2 sensor as a sensor in reading smoke levels with the addition of other components such as a buzzer as warning sign information and LED as an indicator sensor is active. Monitoring media used is the Blynk application on the smartphone in real time when the sensor detects motion and smoke. In this study, the smoke detection system is set to detect smoke with a threshold value of > 100 ppm. The PIR sensor coding and testing program works well and is already integrated with Blynk. In the second measurement, the sensor has an average voltage value on the MQ-2 sensor output on the 3.53 VDC sensor while the PIR sensor measurement when the sensor detects movement of the output voltage is 0 VDC and when the sensor status idle is 3.3 VDC.

An Efficient Smart Streamlet Management System Using Internet of Thing

Waste management is generally handled by the local municipal authority through traditional approaches, but there exist many limitations of these approaches. Considerable number of research has been performed on solid waste management system. However, smart system especially for streamlet waste (liquid) management is unavailable. In this study, we developed an efficient management system for streamlet using Internet of Things. This system informs the concerned municipal authority in real time about the current waste levels of streamlets in a city. For this purpose, sensor kits are deployed over the streamlets that transmit data to the cloud server for storage, processing and analysing via the Internet. The municipal authority can visualise the data in graph-form entries along with a sensor location from the cloud. When the waste level reaches a predefined threshold value, the waste collector is automatically notified through a smart phone in real time. The performance and accuracy of the proposed system is tested based on the conducted case studies. Experimental results show that the proposed system efficiently delivers its desired operations. The implementation of such system in the society will enhance the quality of life and will make opportunities for government and businessmen to invest money on such a project.

Eyelid gestures for people with motor impairments

Although eye-based interactions can be beneficial for people with motor impairments, they often rely on clunky or specialized equipment (e.g., stationary eye-trackers) and focus primarily on gaze and blinks. However, two eyelids can open and close in different orders and for different duration to form rich eyelid gestures. We take a first step to design, detect, and evaluate a set of eyelid gestures for people with motor impairments on mobile devices. We present an algorithm to detect nine eyelid gestures on smartphones in real time and evaluate it with 12 able-bodied people and 4 people with severe motor impairments in two studies. The results of the study with people with motor-impairments show that the algorithm can detect the gestures with .76 and .69 overall accuracy in user-dependent and user-independent evaluations. Furthermore, we design and evaluate a gesture mapping scheme for people with motor impairments to navigate mobile applications only using eyelid gestures. Finally, we discuss considerations for designing and using eyelid gestures for people with motor impairments.

Sistem Pengontrolan dan Monitoring Budidaya Sarang Burung Walet Berbasis Android

Pada pembudidayaan sarang walet, peternak walet mengalami kendala terutama dalam menjaga temperatur suhu dan kelembaban ruangan pada rumah burung walet. Peternak walet harus dapat menjaga kestabilan suhu dan kelembaban serta menjaga keamanan burung walet dari hama burung hantu. Saat suhu panas, ruangan walet akan menjadi kering sehingga sarang menjadi rusak dan burung walet merasa tidak nyaman tinggal pada sarangnya. Berdasarkan hal tersebut, maka dibuat sistem pengontrolan dan monitoring budidaya sarang burung walet berbasis android. Sistem ini dapat membantu menurunkan temperatur suhu dan kelembaban pada ruangan sarang walet menggunakan mesin embun yang bekerja secara otomatis serta pintu ruang walet dapat terbuka/tertutup secara otomatis menggunakan aplikasi pada smartphone. Sistem ini dapat bekerja dengan baik jika diberi tegangan supply AC220V dan DC12V. Mesin embun akan bekerja (ON) jika suhu diatas 29°C atau kelembaban kurang dari 70%. Data hasil pembacaan sensor akan dikirimkan oleh NodeMCU ke server blynk dan ditampilkan pada smartphone. Pintu ruang walet dapat terbuka atau tertutup berdasarkan nilai intensitas cahaya yang terukur pada sensor LDR yang kemudian dikirim ke NodeMCU untuk menggerakkan motor driver dan motor stepper. Dengan adanya sistem ini diharapkan petani dapat memonitoring dan mengontrol kondisi sarang burung walet menggunakan aplikasi blynk pada smartphone secara realtime.
 
 Kata kunci: Sarang Walet, Suhu, Kelembaban, Pintu Ruang Walet, Mesin Embun, Aplikasi blynk.

Sense2Stop: A micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention

BackgroundRelapse to smoking is commonly triggered by stress, but behavioral interventions have shown only modest efficacy in preventing stress-related relapse. Continuous digital sensing to detect states of smoking risk and intervention receptivity may make it feasible to increase treatment efficacy by adapting intervention timing. ObjectiveAims are to investigate whether the delivery of a prompt to perform stress management behavior, as compared to no prompt, reduces the likelihood of (a) being stressed and (b) smoking in the subsequent two hours, and (c) whether current stress moderates these effects. Study designA micro-randomized trial will be implemented with 75 adult smokers who wear Autosense chest and wrist sensors and use the mCerebrum suite of smartphone apps to report and respond to ecological momentary assessment (EMA) questions about smoking and mood for 4 days before and 10 days after a quit attempt and to access a set of stress-management apps. Sensor data will be processed on the smartphone in real time using the cStress algorithm to classify minutes as probably stressed or probably not stressed. Stressed and non-stressed minutes will be micro-randomized to deliver either a prompt to perform a stress management exercise via one of the apps or no prompt (2.5–3 stress management prompts will be delivered daily). Sensor and self-report assessments of stress and smoking will be analyzed to optimize decision rules for a just-in-time adaptive intervention (JITAI) to prevent smoking relapse. SignificanceSense2Stop will be the first digital trial using wearable sensors and micro-randomization to optimize a just-in-time adaptive stress management intervention for smoking relapse prevention.

Real-Time Biomonitoring Device Based on 2D Black Phosphorus and Polyaniline Nanocomposite Flexible Supercapacitors.

Flexible energy storage devices are becoming significantly important to power wearable and portable devices that monitor physiological parameters for many biomedical applications. Many hybrid nanomaterials based on 2D materials are used in order to improve the performance of flexible energy storage devices. Here, a hybrid nanocomposite is synthesized through in situ polymerization of aniline in the presence of black phosphorus (BP) nanoflakes. This nanocomposite, polyaniline (PANI)@BP, is employed to fabricate flexible supercapacitor (FSC) electrodes. PANI@BP FSCs can provide a power source for biometric devices. The generated signal can be transmitted to a smartphone in real time via wireless communication. Such a compact and lightweight integrated device has been used to track a human heart beat while powered by PANI@BP FSC. These findings are providing a promising example of a flexible energy storage device that can be integrated with different real-time health monitoring devices.

Mobile lung cancer early warning based on Windows Azure cloud computing

In view of the repeated investment in the current medical lung cancer early warning system, 'information island' and the low rate of lung cancer early warning, this paper proposes a mobile lung cancer early warning system based on Windows Azure cloud computing with the application requirements of medical information system. The system is applied to the smart phones of Windows system, and the Windows Azure Microsoft cloud platform is accessed through wireless network, using SQL Azure to store medical data (such as lung CT image, ECG curve and high-resolution colour ultrasound image), embed the medical lung cancer early warning model based on deep learning in the cloud computing platform to process and analyse the patient's medical data, and realise the real-time synchronous update of doctors, patients and cloud platform data. The accuracy of lung cancer early-warning system on LIDC-IDRI is high, and the detection results are uploaded to doctors and patients' smart phones in real time. The results show that the mobile lung cancer early warning system based on Windows Azure cloud computing not only effectively integrates medical resources, but also provides patients with medical services and consultation at home, which integrates the advantages of all aspects and adapts to the development of the times.

Mobile lung cancer early warning based on Windows Azure cloud computing

In view of the repeated investment in the current medical lung cancer early warning system, 'information island' and the low rate of lung cancer early warning, this paper proposes a mobile lung cancer early warning system based on Windows Azure cloud computing with the application requirements of medical information system. The system is applied to the smart phones of Windows system, and the Windows Azure Microsoft cloud platform is accessed through wireless network, using SQL Azure to store medical data (such as lung CT image, ECG curve and high-resolution colour ultrasound image), embed the medical lung cancer early warning model based on deep learning in the cloud computing platform to process and analyse the patient's medical data, and realise the real-time synchronous update of doctors, patients and cloud platform data. The accuracy of lung cancer early-warning system on LIDC-IDRI is high, and the detection results are uploaded to doctors and patients' smart phones in real time. The results show that the mobile lung cancer early warning system based on Windows Azure cloud computing not only effectively integrates medical resources, but also provides patients with medical services and consultation at home, which integrates the advantages of all aspects and adapts to the development of the times.

An Abiotic Glucose Indicator System

This study reports the development of an abiotic glucose indicator system constructed using a biofuel cell consisting of a colloidal platinum coated gold microwire (Au-co-Pt) anode and a platinum coated gas diffusion electrode (GDE). The electrochemical and polarization characterizations were achieved via cyclic voltammetry and current-voltage measurements. The biofuel cell demonstrated a maximum open circuit voltage ( $\text{V}_{{\mathrm {oc}}}$ ) of 0.38 V and an $\text{I}_{{\mathrm {sc}}}$ of 0.225 mA/cm2 with $\text{P}_{{\mathrm {max}}}$ of 0.022 mW/cm2 when operating in 5 mM concentration. An optical readout circuit comprising a light emitting diode (LED) and an android mobile phone camera application (App.) were integrated to record glucose concentration levels correlating to the blinking frequency of the LED and transmit the recorded data to a smart phone in real time. When operated as a glucose indicator, the system exhibited a good sensitivity of $0.616~\mu \text{A}$ mM−1 and linear dependence with a correlation coefficient of 0.995 and a wide linear dynamic range up to 50 mM. Excellent selectivity towards glucose in the presence of competing and interfering species was demonstrated. The fabricated abiotic glucose indicator system has the potential to serve as a potentiostat-less platform in point-of-care applications.

Accuracy of Sedentary Behavior-Triggered Ecological Momentary Assessment for Collecting Contextual Information: Development and Feasibility Study.

BackgroundSedentary behavior has received much attention in the scientific community over the past decade. There is growing evidence that sedentary behavior is negatively associated with physical and mental health. However, an in-depth understanding of the social and environmental context of sedentary behavior is missing. Information about sedentary behavior, such as how everyday sedentary behavior occurs throughout the day (eg, number and length of sedentary bouts), where, when, and with whom it takes place, and what people are doing while being sedentary, is useful to inform the development of interventions aimed at reducing sedentary time. However, examining everyday sedentary behavior requires specific methods.ObjectiveThe purpose of this paper is (1) to introduce sedentary behavior–triggered Ecological Momentary Assessment (EMA) as a methodological advancement in the field of sedentary behavior research and (2) to examine the accuracy of sedentary behavior–triggered EMA in 3 different studies in healthy adults. Moreover, we compare the accuracy of sedentary behavior–triggered EMA to simulations of random-trigger designs.MethodsSedentary behavior–triggered EMA comprises a continuous assessment of sedentary behavior via accelerometers and repeated contextual assessments via electronic diaries (ie, an application on a smartphone). More specifically, the accelerometer analyzes and transfers data regarding body position (a sitting or lying position, or an upright position) via Bluetooth Low Energy (BLE) to a smartphone in real time and triggers the deployment of questionnaires. Each time a participant spends a specified time (eg, 20 minutes) in a sedentary position, the e-diary triggers contextual assessments. To test the accuracy of this method, we calculated a percentage score for all triggered prompts in relation to the total number of bouts that could trigger a prompt.ResultsBased on the accelerometer recordings, 29.3% (5062/17278) of all sedentary bouts were classified as moderate-to-long (20-40 minutes) and long bouts (≥ 41 minutes). On average, the accuracy by participant was 82.77% (3339/4034; SD 21.01%, range 71.00-88.22%) on the study level. Compared to simulations of random prompts (every 120 minutes), the number of triggered prompts was up to 47.9% (n=704) higher through the sedentary behavior–triggered EMA approach. Nearly 40% (799/2001) of all prolonged sedentary bouts (≥ 20 minutes) occurred during work, and in 57% (1140/2001) of all bouts, the participants were not alone.ConclusionsSedentary behavior–triggered EMA is an accurate method for collecting contextual information on sedentary behavior in daily life. Given the growing interest in sedentary behavior research, this sophisticated approach offers a real advancement as it can be used to collect social and environmental contextual information or to unravel dynamic associations. Furthermore, it can be modified to develop sedentary behavior–triggered mHealth interventions.

MIT APP INVERTOR PADA APLIKASI SCORE BOARD UNTUK PERTANDINGAN OLAHRAGA BERBASIS ANDROID

Technological developments change various sectors of the world's life that are present in order to facilitate human work in carrying out their daily tasks. An example is an android smartphone that comes with various features as needed. The presence of a competition system that utilizes technology will certainly facilitate the assessment of referees to determine the winner. In addition, it makes it easier for the committee to manage scores by remote control using a smartphone in real time. The match system between branches is certainly different, both in terms of scoring and match time. Therefore the authors build an Android-based application that is integrated with the score board that is used to facilitate the referee to determine the match scores in several sports. Because it is known that each sport has different regulations regarding the scoring system and its time. The results of this study are to produce an application score board using the P10 LED matrix that can be controlled via an Android smartphone. The score board application is made capable of being used in several sports such as futsal, basketball, volleyball and badminton..

Robotic Monitoring of Human and Animal-Real Time and Automated

Autonomous robotic monitoring of human and animal used to secure the house or the flat. This robot can move freely from one side to another side of the house or the flat. Accordingly, this robot is sending the vision to android smartphone in real time. Therefore, the owner of the house or the flat can see inside the house while they were not around. The objective of this research is to develop autonomous robotic to be able to monitor the area from the existing of human and animal and send the vision to android smartphone in real time. This research used four leg robotic as an autonomous robotic monitoring. Four leg robotic is equipped with camera which connected to router based on wireless connection, PIR and ultrasonic sensor and GSM module to send short message service (SMS) notification if PIR sensor detect some movement. The experiment used cat as an animal object. Experiment showed that this robot can follow the object, either a human or an animal, within range of 10–45 cm from robot in 12 seconds and send the vision to android smartphone in real-time. The SMS is received in 5 seconds after camera capture the object. This robotic cannot determine who is the object on the camera because it is not equipped with object detection system.

Real‐time crack assessment using deep neural networks with wall‐climbing unmanned aerial system

AbstractCrack information provides important evidence of structural degradation and safety in civil structures. Existing inspection methods are inefficient and difficult to rapidly deploy. A real‐time crack inspection method is proposed in this study to address this difficulty. Within this method, a wall‐climbing unmanned aerial system (UAS) is developed to acquire detailed crack images without distortion, then a wireless data transmission method is applied to fulfill real‐time detection requirements, allowing smartphones to receive real‐time video taken from the UAS. Next, an image data set including 1,330 crack images taken by the wall‐climbing UAS is established and used for training a deep‐learning model. For increasing detection speed, state‐of‐the‐art convolutional neural networks (CNNs) are compared and employed to train the crack detector; the selected model is transplanted into an android application so that the detection of cracks can be undertaken on a smartphone in real time. Following this, images with cracks are separated and crack width is calculated using an image processing method. The proposed method is then applied to a building where crack information is acquired and calculated accurately with high efficiency, thus verifying the practicability of the proposed method and system.