Design of The WBAN in The Mobile Health Monitoring System

WBAN (Wireless Body Area Network) technology is used in this study to provide an integrated health monitoring platform. The device utilizes MLX90615 for measuring body temperature, a Blood Pressure Sensor for measuring blood pressure and pulse rate, and a MAX30102 Sensor for measuring blood oxygen and blood glucose levels. The output of this utility is displayed on an OLED screen and is controlled by the NODEMCU ESP8266. The test reveals an accuracy of 94.8%, indicating that the instrument can provide accurate results and has a relatively low error rate on each sensor. Heart Rate Error on Blood Pressure Sensor 0; Spo2 Error on MAX 30102 Sensor 1; and Blood Sugar Error on MAX 30102 Sensor 2.0. Real-time health monitoring that is more accurate and efficient. This device has the potential to be a practical solution for routine health monitoring and provides significant benefits for maintaining health

Sistem Navigasi pada Mobile Robot dengan Global Positioning System (GPS)

This paper present the use of Global Positioning Systems (GPS) as navigational system for a ground based mobile robot. The proposed mobile robot contains a GPS system for navigation and sensors utrasonic for obstacle avoidance system. The Mobile robot navigates to the waypoint specified by the user through communication system xbee and avoids the obstacles in its way to destination. Mobile Robot can navigate through desired waypoint and at the same time apply the obstacle avoidance rule

Performance Evaluation on Applied Low-Cost Multi-Sensor Technology in Air Pollution Monitoring

This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals.  In this study, we investigated the performance of a custom-built prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area.  The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution. &nbsp

Sistem Kendali Fuzzy pada Mobile Robot

Implementasi sistem kendali fuzzy pada mobile robot dengan sistem berjalan secara otomatis, agar kendali mobile robot tetap pada jalur jalan dan melaju dengan kecepatan tertentu. Untuk menjaga agar tetap berada pada jalur, mobile robot mengambil data jarak dari sensor ultrasonik. Dengan menggunakan sistem kendali logika fuzzy, yang diberikan sinyal kendali pada kedua motor untuk mengurangi atau menambah kecepatannya. Jika di depan terdapat rintangan lain yang kecepatannya lebih rendah maka sistem kendali logika fuzzy akan selalu menjaga jarak aman dengan mengatur kecapatannya. Sistem Logika Fuzzy dipilih sebagai pengendali karena mampu bekerja baik pada sistem non-linear dan menawarkan kemudahan dalam perancangan program karena tidak memerlukan model matematis dari sistem. Kombinasi tersebut bertujuan untuk menghasilkan respon pergerakan yang halus (smooth) dalam bernavigasi pada lingkungan yang tidak diketahui. Pergerakan mobile robot dan lingkungan yang tidak diketahui, dengan kondisi bebas hambatan dan ada hambatan

PENGENALAN KONTUR TANGAN PADA PENGKODEAN BAHASA ISYARAT BAGI PENDERITA TUNA RUNGU WICARA DENGAN MENGGUNAKAN METODE SHAPE BASED HAND GESTURE

Tuna rungu wicara merupakan kehilangan kemampuan mendengar yang disertai tidak mampu mengembangkan kemampuan bicaranya dalam kehidupan sehari-hari untuk melakukan komunikasi.Ketidakmampuan untuk berkomunikasi dengan normal membuat para penderita tuna rungu dan tuna wicara sulit untuk diterima dalam komunitas mayoritas normal.Sedangkan komunikasi yang digunakan adalah Sistem Isyarat Bahasa Indonesia (SIBI), dengan komunikasi isyarat menggunakan pergerakan tangan (Hand Gesture).Kelemahan jenis komunikasi ini adalah sering tejadi kesalapahaman dan keterbatasan, dikarenakan bahasa isyarat umumnya hanya dimengerti oleh kelompok minoritas. Untuk membantu melakukan komunikasi dengan efektif secara real time, maka perlu adanya alat komunikasi dua arah yang dapat digunakan untuk mengkodekan pola hand gesture menjadi teks, image dan suara supaya dapat dimengerti oleh semua orang. Dalam penelitian ini memfokuskan pada Hand Gesture Recognition menggunakan Algoritma Shape Based Hand dimana metode ini mengklasifikasikan image berdasarkan kontur tangan dengan menggunakan jarak Hausdorff dan jarak Euclidean, untuk menentukan tingkat kemiripan antara dua tangan berdasarkan jarak terpendek. Hasil dari pengujian ini dapat mengenali 26 huruf isyarat, tingkatakurasi pengenalan bahasa isyarat tangan 85%,pada image tangan orang yang berbeda, yang diambil pada sesi yang berbeda dengan kondisi pencahayan serta jarak image ke kamera. Serta dapat mengenali 70% kontur tangan yang berbeda dari sample yang diambil. Dengan menggunakan metode ini dibandingkan dengan penelitian lain, adalah semakin banyak jumlah objek (kontur tangan) yang digunakan, maka terdapat sedikit klasifikasi ukuran tangan. Sehingga dengan mengunakan metode ini ukuran tangan dapat diminimalisir, apabila menggunakan subjek yang banyak.Kata Kunci :kontur tangan, bahasa isyarat, metode shape based hand gesture, jarak Hausdorff, jarak Euclidean

Littering Activities Monitoring using Image Processing

Littering is a human behavior that become a habit since childhood. Even though there are rules that prohibit this behavior, the community still continues to do so. In order to limit this bad behavior, a device that can monitor and provide notifications is needed. In this research, a device is offered that can identify human activities in real time using webcam-based image processing. Then, it is processed by machine learning using the Recurrent Neural Network (RNN). The monitoring device produced in this research works by comparing the captured image data with a dataset. The captured image data will then be extracted features and form several coordinate points on the human body, then the system will classify these human activities into the category of normal activities or littering activities. This device will provide an output in the form of a warning every time the activity of littering is detected. &nbsp

Brief Review on Formation Control of Swarm Robot

This paper presented review formation control ofswarm robot. Recently the problems formation control of swarmrobots has attracted much attention, and several formationcontrol schemes were proposed based on various strategies. Theformation control strategies to solved these problem on swarmrobots, with considering regulation concept in control theory.Swarm intelligence algorithms takes the full of advantages of thefeature of swarm robotics, and provides a great solution forproblem formation control on swarm robots

The Implementation of Mobile Technology in The Process of Reporting Disasters and Events

Telecommunications have an important role in facilitating communication and information exchange, especially in emergency situations such as natural disasters and unexpected community events. Implementing mobile technology is a promising solution to improve the response and handling of in-kind problems. Mobile technology allows the public to quickly report incidents of disaster or security issues through applications or short message services. The implementation of mobile technology facilitates real-time communication between the community and Babinsa. The public can send reports quickly, convey important information, and share photos or videos as evidence of events. Babinsa, on the other hand, can respond more efficiently to these reports and take necessary actions based on the information received. Apart from that, mobile technology also supports two-way communication between Babinsa and the community. The public can also get the latest information about emergencies, efforts handling, or evacuation via app or direct message notification. Thus, the implementation of mobile technology can make a significant contribution to improving communication, response, and handling of disasters and community events

Environmental Application with Multi Sensor Network

This paper aimed to monitor temperature, humidity, and CO gas level using environmental application with multi sensor network (MSN). This system was applied in real life and real time, to be able to obtain data and information through mobile devices and other on internet network. In this research, environmental application is monitored remotely using displays on the web and sensors as device. This research obtained data in outdoor and indoor parking area also with obstacles and without obstacles, so it obtained the results from each of the different environmental conditions.   &nbsp

Implementasi CRISP-DM Model Menggunakan Metode Decision Tree dengan Algoritma CART untuk Prediksi Curah Hujan Berpotensi Banjir

Indonesia is part of a tropical climate with high rainfall intensity. High rainfall intensity can potentially cause flooding. To minimize this, accurate weather predictions are needed to be able to anticipate beforehand. This research was conducted with the aim of classifying based on the rain category with the dichotomy of heavy rain and very heavy rain using data mining techniques with the CRISP-DM methodology. The algorithm used in the classification technique is CART (Classification And Regression Tree) with Confusion Matrix test parameters. Based on the results of the model evaluation, it shows that the CART algorithm has a fairly good performance in classifying with an accuracy value of 89.4%