EMBOF-RPL: Improved RPL for early detection and isolation of rank attack in RPL-based internet of things

2022 ◽  
Author(s):  
A. O. Bang ◽  
Udai Pratap Rao
Keyword(s):  
Internet Of Things ◽  
Early Detection

A Survey on Early Detection of Women's Breast Cancer Using IoT

2021 ◽  
pp. 208-219
Author(s):  
P. Malathi ◽  
A. Kalaivani
Keyword(s):  
Breast Cancer ◽  
Internet Of Things ◽  
Early Detection ◽  
Time Data ◽  
Diagnose Breast Cancer ◽  
Current State ◽  
Past Data ◽  
Self Examination ◽  
The Internet Of Things ◽  
Detect Breast Cancer

The internet of things is probably one of the most challenging and disruptive concepts raised in recent years. Recent development in innovation and availability have prompted the rise of internet of things (IoT). IoT technology is used in a wide scope of certified application circumstances. Internet of things has witnessed the transition in life for the last few years which provides a way to analyze both the real-time data and past data by the emerging role. The current state-of-the-art method does not effectively diagnose breast cancer in the early stages. Thus, the early detection of breast cancer poses a great challenge for medical experts and researchers. This chapter alleviates this by developing a novel software to detect breast cancer at a much earlier stage than traditional methods or self-examination.

Pengembangan Smart Home Dengan Microcontrollers ESP32 Dan MC-38 Door Magnetic Switch Sensor Berbasis Internet of Things (IoT) Untuk Meningkatkan Deteksi Dini Keamanan Perumahan

2019 ◽  
Vol 3 (3) ◽  
pp. 451-457
Author(s):  
Andi Setiawan ◽  
Ade Irma Purnamasari
Keyword(s):  
Internet Of Things ◽  
Early Detection ◽  
Early Warning ◽  
Smart Home ◽  
Detection System ◽  
The Internet ◽  
Magnetic Switch ◽  
Web Framework ◽  
Closed Angle ◽  
The Internet Of Things

The objective developed from this research is to utilize Smart Home with an integrated ESP32 microcontroller with a camera and MC-38 door magnetic switch sensor based on the Internet of Things (IoT) as a research base to detect the security of arumsari earth housing in Cirebon District when left by its inhabitants. ESP32 microcontroller which can be programmed via arduino IDE, then functioned to respond to the integrated camera so that it can transmit images when the MC-38 sensor door magnetic switch sensor is active. Technically the combination of the ESP32 microcontroller and MC-38 door magnetic switch sensor, which was developed as a prototype in this study is called the arumsari housing early detection system. The mechanism of the arumsari housing early detection system is when a house door or window is successfully forcibly broken without going through the system mechanism, then automatically an image or can also be developed into a video from a camera mounted on an ESP32 microcontroller will send the image through a web framework or smartphone as a form early warning of security to housing owners. The results obtained from this study are at the angle of normally open MC-38 door magnetic switch sensor of 60 - 1800, will work sending an image signal which means there is an indication of a burglar or unknown person entering the house. Whereas at the normally closed angle MC-38 door magnetic switch sensor is 00-50, it will not work sending an image signal which means the house is safe.

Role of the Internet of Things for Early Detection of Covid-19 Infections: a Comprehensive Survey

2021 ◽  
Author(s):  
Sanjoy Mondal ◽  
Indrakshi Ghosh ◽  
Sayak Ghosh ◽  
Ayushi Gupta ◽  
Dipankar Basu
Keyword(s):  
Internet Of Things ◽  
Early Detection ◽  
The Internet ◽  
Comprehensive Survey ◽  
The Internet Of Things

Application of Internet of Things for Early Detection of COVID-19 using Wearables

2021 ◽  
Author(s):  
Taki Uddin ◽  
Md. Borhan Uddin ◽  
A.K.M. Muzahidul Islam ◽  
Salekul Islam ◽  
Swakkhar Shatabda
Keyword(s):  
Internet Of Things ◽  
Early Detection

scholarly journals Internet of things based Early Detection of Diabetes using Machine Learning Algorithms: Dpa

2019 ◽  
Vol 8 (10) ◽  
pp. 1443-1447
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Early Detection ◽  
Decision Tree ◽  
Machine Learning Algorithms ◽  
Prediction Algorithm ◽  
Early Prediction ◽  
Decision Tree Algorithm ◽  
Diabetes Prediction ◽  
Prediction Of Diabetes

This paper introduces a new decision tree algorithm Diabetes Prediction Algorithm (DPA), for the early prediction of diabetes based on the datasets. The datasets are collected by using Internet of Things (IOT) Diabetes Sensors, comprises of 15000 records, out of which 11250 records are used for training purpose and 3750 are used for testing purpose. The proposed algorithm DPA yielded an accuracy of 90.02 %, specificity of 92.60 %, and precision of 89.17% and error rate of 9.98%. further, the proposed algorithm is compared with existing approaches. Currently there are numerous algorithms available which are not complete accurate and DPA helps.

scholarly journals Monitoring of Various Crucial Parameters and Control of Salinity Damage in Banana Crop (Banntex) using WSN and IoT

2020 ◽  
Vol 8 (6) ◽  
pp. 693-699
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Early Detection ◽  
Wireless Sensor ◽  
Soil Parameters ◽  
Banana Fruit ◽  
And Control ◽  
Banana Crop

In India 60 percent of total cultivated land is fully dependent on rain and if there is less than average rain fall than it results into significant reduction in the overall agricultural production and it leads heavy losses to farmers and ultimately it affects the overall gross domestic production of India. Banana is an important fruit and it is one of good cash crop in India. In this research work, our aim is to design and implement Banana Crop System (Banntex) to sense crucial parameters and early detection of diseases and control using Wireless Sensor Networks (WSN) and Internet of Things (IoT). To implement Banntex we uses advancement of new technology like Internet of Things (IoT), Sensors development and Improved Wireless Sensor Networks, we can design and developed Precision Agriculture systems in which various sensors are used to measure the different parameters like temperature of air and soil, relative humidity, water potential of banana field, pH value of soil, Electric conductivity of soil, salinity of banana field soil, Moisture changes in soil, soil quality, fertility of soil, ground water quality and crop growth. Based on the measured parameters this system can be used to control and automate the farming processes. This precision system empowers farmers to keep updated, early detection of soil parameters and take necessary steps to improve it further. It results to improve the biomass, roots and overall growth of banana crops and finally it increases productivity and improved quality of farming with minimum manual tasks. Experimental results will show the significant improvement in the Banana crop production and Quality of Banana Fruit using our proposed Banntex System.

scholarly journals GRADIENT BOOSTING ALGORITHM FOR EARLY DETECTION OF UNKNOWN INTERNET OF THINGS DEVICES

2021 ◽  
Vol 25 (Special) ◽  
pp. 1-115-1-126
Author(s):  
Vian A. Ferman ◽  
◽  
Mohammed A. Tawfeeq ◽  
Keyword(s):  
Internet Of Things ◽  
Early Detection ◽  
Cyber Attacks ◽  
Identification Accuracy ◽  
Gradient Boosting ◽  
Network Protection ◽  
Boosting Algorithm ◽  
Iot Devices ◽  
Setup Phase ◽  
The Internet Of Things

The pervasive availability of the Internet of Things (IoT) markets lures targets for cyber-attacks since most manufactured IoT devices are usually resource-constrained devices. The first powerful line of IoT network protection from these vulnerabilities is detecting IoT devices especially the unauthorized ones by utilizing machine learning (ML) algorithms. Actually, it is so difficult or even impossible to find individual unknown IoT devices during the setup phase but, knowing their manufacturers is a matter to be deliberate. In this paper, a new method based fingerprints generation is introduced to detect the connected devices in the setup phase. Fingerprints for 21 different IoT devices are generated using devices’ network traffic. The whole produced fingerprints of devices are divided into four groups according to their manufacturers or fingerprints similarity proportion. Gradient Boosting Algorithm is applied to achieve the identified purposes. The proposed method is considered as a preparatory study for early detection of unauthorized. The performance evaluation for the proposed method was calculated based on two metrics: Identification accuracy and F1-score. The average identification accuracy rate was around 98.65%, while the average F1-score was about 99%.

scholarly journals WSN and IoT Based Monitoring of Various Macronutrient Parameters and Disease Control of Banana Crop

2020 ◽  
Vol 9 (5) ◽  
pp. 1290-1296
Keyword(s):  
Internet Of Things ◽  
Early Detection ◽  
Precision Agriculture ◽  
Banana Fruit ◽  
Complete Control ◽  
On Line ◽  
Manual Tasks ◽  
And Control ◽  
Banana Crop

In India, banana is an important fruit. In this research, we designed and develop a precision agriculture system to monitor the various macronutrients and various crucial parameters to control and early detection of various diseases of banana crop using Wireless Sensor Networks (WSN) and Internet of Things (IoT). Developed precision agriculture system is used various sensors to sense and measure various micronutrients like Magnesium (Mg), Calcium (Ca), Sulfur (S), nitrite content in soil, ground water quality, crop growth, pest detection, crop on line monitoring, animal intrusion into the field and so on. It also measures the different parameters like change in weather, temperature, humidity, moisture changes in soil, quality and fertility of soil, various weeds, and level of water. Precision agriculture system implemented using advance sensors and improved technologies like WSN, IoT. Research experimental results show significant improvement in quality of banana fruit and overall production of banana crop. Before design and implementation we have carried out a detailed literature review on various approaches of precision monitoring system using Internet of Things (IoT). Proposed precision agriculture system can be used to automate and complete control of all farming processes. Our major focused is on monitoring macronutrients like Magnesium (Mg), Calcium (Ca) and Sulfur (S) parameters, to supply balance macronutrients using automatic action and early detection of diseases and control of Banana Crops System which will result to increase the productivity and quality of Banana products. This precision agriculture system keep farmers/users updated and empowers with minimum manual tasks.

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