Real-time Environment Monitoring System using ESP8266 and ThingSpeak on Internet of Things Platform

Author(s):  
Debapriya Parida ◽  
Asish Behera ◽  
Jagdish Kumar Naik ◽  
Soumyaranjan Pattanaik ◽  
Rajat Sekhar Nanda
2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia

Diabetes merupakan penyakit “silent killer” yang ditandai dengan peningkatan kadar glukosa darahdan kegagalan sekresi insulin. World Health Organization (WHO) pada tahun 2016 menyatakanbahwa diabetes menduduki urutan ke-6 sebagai penyakit mematikan di Indonesia. Sehingga upayapencegahan dan penanganan diabetes perlu mendapat perhatian yang serius. Internet of Things (IoT)dapat dijadikan sarana penunjang dalam penanganan penyakit diabetes. Inovasi ini memungkinkanperangkat perawatan kesehatan terhubung dengan jaringan internet, sehingga data pasien dapatdiperbaharui dan diakses secara real-time. Selain mempermudah akses, penggunaan IoT juga akanmemberikan nilai tambah pada efisiensi biaya pelayanan kesehatan. Penelitian ini bertujuan untukmerancang software sistem monitoring gula darah berbasis web yang terintegrasi dengan IoT,sehingga pasien dapat melakukan pemeriksaan, konsultasi dengan dokter dan melihat data rekammedis dari jarak jauh. Data hasil pemeriksaan akan disimpan didalam cloud dan ditampilkan secaraonline. Penelitian ini menggunakan Node MCU ESP8266 sebagai mikrokontroller yang telahdilengkapi dengan modul WiFi, Thingspeak sebagai cloud, aplikasi online dengan “Diamons” sebagaidashboard yang mampu menampilkan presentasi data grafis, dibangun dengan bahasa HypertextPreprocessor (PHP) sebagai bahasa pemogramannya. Penelitian ini akan melibatkan pihak medisdalam pengambilan keputusan. Umpan balik yang diberikan kepada pasien berupa anjuran sepertiresep obat, pola makan, dan kegiatan fisik yang harus dilakukan oleh pasien.


Author(s):  
Supun Athukorala ◽  
Irunika Weeraratne ◽  
Dumindu Jayathilaka ◽  
Asitha Bandaranayake ◽  
Roshan Ragel

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Chen ◽  
Xiao Hao ◽  
JianRong Lu ◽  
Kui Yan ◽  
Jin Liu ◽  
...  

In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.


2020 ◽  
Vol 21 (1) ◽  
pp. 56-67
Author(s):  
Husneni Mukhtar ◽  
Doan Perdana ◽  
Parman Sukarno ◽  
Asep Mulyana

ABSTRACTThe needs of flood disaster management encourage various efforts from all scientific disciplines of science, technology, and society. This article discusses the efforts to prevent flooding due to the habit of disposing of their waste into rivers through an innovative waste management system using the approach and application of Internet-based technology (IoT). Previous research has produced a prototype of the waste level monitoring system. In this research, the prototype was developed into a practical technology, called SiKaSiT (IoT Based Trash Capacity Monitoring System). This technology aims to assist janitor in monitoring, controlling and obtaining information about trash capacity and disposal time easily through an application on the smartphone in real-time and online. The system was made using a level detection sensor integrated with NodeMCU and Wi-Fi, MQTTbroker-protocol and Android-based application. Furthermore, the system was implemented in Bojongsoang adjacent to the Citarum river, where the water often overflowed due to the high rainfall and volume of trash around it. The results of system testing in the field shown good performance with value ranges of reliability is (99,785 - 99,944)% and availability is (99,786 - 99,945)%. SiKaSiT has several advantages over other similar systems. First, there is an application on the user's smartphone to monitor the capacity of trash and notification for full-bin. Second, the ability to operate on a small-bandwidth internet network because the throughput time is only around 0.59 kbps, thereby saving internet bandwidth consumption. This system has also helped overcome the problem of community trash management in Kampung Cijagra, where 60% of them gave feedback "agree" and the rest "strongly agree".Keywords: waste, IoT, monitoring, flooding, riverABSTRAKKebutuhan penanggulangan bencana banjir mendorong berbagai upaya dari semua disiplin ilmu baik dari bidang sains, teknologi dan sosial. Dalam artikel ini, penulis membahas upaya pencegahan banjir akibat kebiasaan membuang sampah ke sungai melalui inovasi sistem manajemen sampah menggunakan pendekatan dan penerapan teknologi berbasis Internet of Things (IoT). Pada riset sebelumnya telah dihasilkan sebuah prototype sistem monitoring level sampah. Kemudian pada riset ini prototype tersebut dikembangkan menjadi suatu teknologi tepat guna, dinamakan dengan SiKaSiT (Sistem Pemantauan Kapasitas Sampah Berbasis IoT). Teknologi ini bertujuan untuk membantu petugas kebersihan dalam memantau, mengontrol dan memperoleh informasi tentang kapasitas sampah dan waktu pembuangan sampah dengan mudah melalui aplikasi di smartphone secara real time dan online. Sistem dibuat dengan menggunakan sensor deteksi ketinggian sampah yang diintegrasikan dengan NodeMCU dan Wi-Fi, protokol MQTT broker dan aplikasi berbasis android pada smartphone. Selanjutnya sistem diimplementasikan di daerah Bojongsoang yang berdekatan dengan sungai Citarum yang airnya sering meluap akibat tingginya curah hujan dan volume sampah di sekitarnya. Hasil pengujian sistem di lapangan menunjukkan kinerja yang baik dengan kisaran nilai reliability adalah (99,785 – 99,944) % dan availability adalah (99,786 – 99,945) %. SiKaSiT memiliki beberapa kelebihan dibanding sistem serupa lainnya. Pertama, adanya aplikasi di smartphone pengguna untuk memonitor kapasitas sampah dan notifikasi saat tempat sampah penuh. Kedua, sistem mampu beroperasi pada jaringan internet bandwith kecil karena waktu throughput-nya hanya sekitar 0,59 kbps sehingga menghemat konsumsi bandwith internet. Sistem ini juga telah membantu menanggulangi permasalahan pengelolaan sampah masyarakat Kampung Cijagra, dimana 60% masyarakat memberi feedback “setuju” dan sisanya “sangat setuju”.Kata kunci: Sampah, IoT, Monitoring, Banjir, Sungai


2020 ◽  
Vol 16 (7) ◽  
pp. 155014772094403
Author(s):  
Yuan Rao ◽  
Min Jiang ◽  
Wen Wang ◽  
Wu Zhang ◽  
Ruchuan Wang

Intensive animal husbandry is becoming more and more popular with the adoption of modern livestock farming technologies. In such circumstances, it is required that the welfare of animals be continuously monitored in a real-time way. To this end, this study describes one on-farm welfare monitoring system for goats, with a combination of Internet of Things and machine learning. First, the system was designed for uninterruptedly monitoring goat growth in a multifaceted and multilevel manner, by means of collecting on-farm videos and representative environmental data. Second, the monitoring hardware and software systems were presented in detail, aiming at supporting remote operation and maintenance, and convenience for further development. Third, several key approaches were put forward, including goat behavior analysis, anomaly data detection, and processing based on machine learning. Through practical deployment in the real situation, it was demonstrated that the developed system performed well and had good potential for offering real-time monitoring service for goats’ welfare, with the help of accurate environmental data and analysis of goat behavior.


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