scholarly journals IOTFlood: hardware and software platform using internet of things to monitor floods in real time

2021 ◽  
Vol 16 (4) ◽  
pp. 1
Author(s):  
Francisco Vital Da Silva Júnior ◽  
Mônica Ximenes Carneiro Da Cunha ◽  
Marcílio Ferreira De Souza Júnior
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Research Design ◽  
Open Source Software ◽  
Low Cost ◽  
Sensor Data ◽  
Software Platform ◽  
Web Interface ◽  
Iot Platform

Floods are responsible for a high number of human and material losses every year. Monitoring of river levels is usually performed with radar and pre-configured sensors. However, a major flood can occur quickly. This justifies the implementation of a real-time monitoring system. This work presents a hardware and software platform that uses Internet of Things (IoTFlood) to generate flood alerts to agencies responsible for monitoring by sending automatic messages about the situation of rivers. Research design involved laboratory and field scenarios, simulating floods using mockups, and later tested on the Mundaú River, state of Alagoas, Brazil, where flooding episodes have already occurred. As a result, a low-cost, modular and scalable IoT platform was achieved, where sensor data can be accessed through a web interface or smartphone, without the need for existing infrastructure at the site where the IOTFlood solution was installed using affordable hardware, open source software and free online services for the viewing of collected data.

Application of WeChat Mini-Program and Wi-Fi SoC in Agricultural IoT: A Low-Cost Greenhouse Monitoring System

2020 ◽  
Vol 63 (2) ◽  
pp. 325-337
Author(s):  
Lei Zhou ◽  
Zhengjun Qiu ◽  
Yong He
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
High Performance ◽  
Low Cost ◽  
Rapid Development ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Smart Devices ◽  
Increasing Demand ◽  
On Chip

HighlightsA quick solution for developing and deploying custom agricultural IoT systems is proposed.Low-cost and high-performance devices are used for the design of sensor nodes.A mobile application based on WeChat Mini-Program is developed for device and data management.The proposed system brings convenience to both users and developers.Abstract. Increasing demand for automatic management of agricultural production and real-time remote monitoring has increased the need for smart devices, wireless technologies, and sensors. The internet of things (IoT) has emerged as a common technology for the management of multiple devices by multiple users. Some professional solutions are relatively difficult to implement for researchers who are interested in agricultural IoT but do not have requisite skills in computers and electronics. The unfriendliness of the user software limits the practical application of agricultural IoT in China. This article presents a simple solution based on an SoC (system-on-chip) and WeChat mini-program that focuses on low-cost hardware, rapid development, user-friendly application design, and helping developers get a quick start in building a DIY monitoring system. The ESP8266, a high-performance SoC, is used as the microcontroller and Wi-Fi module to transfer the sensor data to a remote server. A WeChat mini-program provides the graphical user interface, enabling users to manage devices and access data by clicking. Users can log into the system using their WeChat accounts and bind devices by scanning QR codes on the devices. Thus, the complex management and device binding in conventional systems can be overcome. The system is easy to be expand and has great potential for greenhouse environmental monitoring in China. Keywords: Greenhouse ambient monitoring, Internet of things, WeChat mini-program, Wi-Fi SoC.

Perancangan Sistem Informasi “DIAMONS” (Diabetes Monitoring System) Berbasis Internet of Things (IoT)

2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia
Keyword(s):  
Internet Of Things ◽  
World Health Organization ◽  
Real Time ◽  
Monitoring System ◽  
World Health ◽  
Health Organization ◽  
Diabetes Monitoring

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.

Smart and Low Cost Real Time Water Quality Monitoring System Using IoT

2019 ◽  
Author(s):  
Jeba Anandh S ◽  
Anandharaj M ◽  
Aswinrajan J ◽  
Karankumar G ◽  
Karthik P
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring

scholarly journals Design of Early Warning System Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 66
Author(s):  
Gan Bo ◽  
Jin Shan
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Sensor Data ◽  
Landslide Monitoring ◽  
Remote Transmission ◽  
Sensor Data Acquisition

In order to solve the shortcomings of the landslide monitoring technology method, a set of landslides monitoring and early warning system is designed. It can achieve real-time sensor data acquisition, remote transmission and query display. In addition, aiming at the harsh environment of landslide monitoring and the performance requirements of the monitoring system, an improved minimum hop routing protocol is proposed. It can reduce network energy consumption, enhance network robustness, and improve node layout and networking flexibility. In order to realize the remote transmission of data, GPRS wireless communication is used to transmit monitoring data. Combined with remote monitoring center, real-time data display, query, preservation and landslide warning and prediction are realized. The results show that the sensor data acquisition system is accurate, the system is stable, and the node network is flexible. Therefore, the monitoring system has a good use value.

Intelligent Environmental Monitoring System Based on Multi-Sensor Data Technology

2020 ◽  
Vol 11 (4) ◽  
pp. 57-71
Author(s):  
Qiuxia Liu
Keyword(s):  
Data Fusion ◽  
Environmental Monitoring ◽  
Real Time ◽  
Monitoring System ◽  
Intelligent System ◽  
Evidence Synthesis ◽  
Environmental Parameters ◽  
Monitoring Data ◽  
Sensor Data ◽  
Environmental Monitoring System

Using multi-sensor data fusion technology, ARM technology, ZigBee technology, GPRS, and other technologies, an intelligent environmental monitoring system is studied and developed. The SCM STC12C5A60S2 is used to collect the main environmental parameters in real time intelligently. The collected data is transmitted to the central controller LPC2138 through the ZigBee module ATZGB-780S5, and then the collected data is transmitted to the management computer through the GPRS communication module SIM300; thus, the real-time processing and intelligent monitoring of the environmental parameters are realized. The structure of the system is optimized; the suitable fusion model of environmental monitoring parameters is established; the hardware and the software of the intelligent system are completed. Each sensor is set up synchronously at the end of environmental parameter acquisition. The method of different value detection is used to filter out different values. The authors obtain the reliability of the sensor through the application of the analytic hierarchy process. In the analysis and processing of parameters, they proposed a new data fusion algorithm by using the reliability, probability association algorithm, and evidence synthesis algorithm. Through this algorithm, the accuracy of environmental monitoring data and the accuracy of judging monitoring data are greatly improved.

scholarly journals A study on the development of a light scattering particulate matter sensor and monitoring system

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho
Keyword(s):  
Big Data ◽  
Particulate Matter ◽  
Light Scattering ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Gravimetric Method ◽  
Correction Method ◽  
Measurement Methods ◽  
Linear Correction

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

scholarly journals Sistem Pemantauan Kapasitas Sampah Berbasis IoT (SiKaSiT) untuk Pencegahan Banjir di Wilayah Sungai Citarum Bojongsoang Kabupaten Bandung

2020 ◽  
Vol 21 (1) ◽  
pp. 56-67
Author(s):  
Husneni Mukhtar ◽  
Doan Perdana ◽  
Parman Sukarno ◽  
Asep Mulyana
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Disaster Management ◽  
Throughput Time ◽  
Science Technology ◽  
Scientific Disciplines ◽  
Small Bandwidth ◽  
Strongly Agree ◽  
Level Monitoring

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

scholarly journals An IoT based Low-cost Weather Monitoring System for Smart Farming

2021 ◽  
Author(s):  
L.P.S.S.K. Dayananda ◽  
A. Narmilan ◽  
P. Pirapuraj
Keyword(s):  
Liquid Crystal ◽  
Mobile Phone ◽  
Real Time ◽  
Monitoring System ◽  
Liquid Crystal Display ◽  
Low Cost ◽  
Weather Conditions ◽  
Weather Data ◽  
The Internet ◽  
Arduino Uno

Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions. Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. Result: This is a low-cost smart weather monitoring system. This system’s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer’s mobile phone, allowing him to make better decisions to increase yield.

scholarly journals AdaGUM: An Adaptive Graph Updating Model-Based Anomaly Detection Method for Edge Computing Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Yu ◽  
Chun Shan ◽  
Jilong Bian ◽  
Xianfei Yang ◽  
Ying Chen ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Anomaly Detection ◽  
Real Time ◽  
Detection Method ◽  
Edge Computing ◽  
Sensor Data ◽  
Computing Environment ◽  
The Real ◽  
Edge Node ◽  
Model Based

With the rapid development of Internet of Things (IoT), massive sensor data are being generated by the sensors deployed everywhere at an unprecedented rate. As the number of Internet of Things devices is estimated to grow to 25 billion by 2021, when facing the explicit or implicit anomalies in the real-time sensor data collected from Internet of Things devices, it is necessary to develop an effective and efficient anomaly detection method for IoT devices. Recent advances in the edge computing have significant impacts on the solution of anomaly detection in IoT. In this study, an adaptive graph updating model is first presented, based on which a novel anomaly detection method for edge computing environment is then proposed. At the cloud center, the unknown patterns are classified by a deep leaning model, based on the classification results, the feature graphs are updated periodically, and the classification results are constantly transmitted to each edge node where a cache is employed to keep the newly emerging anomalies or normal patterns temporarily until the edge node receives a newly updated feature graph. Finally, a series of comparison experiments are conducted to demonstrate the effectiveness of the proposed anomaly detection method for edge computing. And the results show that the proposed method can detect the anomalies in the real-time sensor data efficiently and accurately. More than that, the proposed method performs well when there exist newly emerging patterns, no matter they are anomalous or normal.

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