scholarly journals FLOOD AVOIDANCE USING IOT

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Jasmin Maurya ◽  
Hemlata Pant ◽  
Shivani Dwivedi ◽  
Muskan Jaiswal
Keyword(s):  
Detection System ◽  
Weather Condition ◽  
Weather Conditions ◽  
Water Bodies ◽  
The Internet ◽  
Common People ◽  
The People ◽  
Temperature And Humidity ◽  
Flood Detection ◽  
The Internet Of Things

Flood is a common problem not only in India but worldwide and most of the water bodies are easily accessible to common people. At times it may happen that the weather conditions may change suddenly and the water bodies may become violent, resulting in a flood which can lead to loss of lives as well as livestock. Therefore, a rapid flood detection system that can reach a wide area such as the internet is necessary to minimize the effects of disasters. So, this paper proposes a flood detection system with the help of the Internet of Things (IoT). IoT is a smart technology that has the capability to send data in realtime. The system is powered using Arduino and has 3 sensors to detect 5 different parameters. Firstly, to measure temperature and humidity we have DHT-11 Digital Temperature and Humidity Sensor. Then we have the Water Flow sensor to check the flow of water. And lastly, to measure the distance and water level we have HC-SR04-Ultrasonic Range Finder and Distance Sensor. Finally, the collected information is transmitted to LCD to display the information. The system continuously keeps checking any changes in the weather condition and updates the live data over IoT. In case the parameters reach a dangerous level the system immediately alerts the people.

scholarly journals A Study on Iot Based Flood Detection Management System

2021 ◽  
Vol 10 (4) ◽  
pp. 130-133
Author(s):  
C.K. Gomathy ◽  
Priya, G G Lasya ◽  
Hemanth Kumar
Keyword(s):  
Mobile App ◽  
Water Levels ◽  
The Internet ◽  
Time Data ◽  
The Past ◽  
The People ◽  
The World ◽  
Flood Detection ◽  
The Internet Of Things ◽  
Different Parts

Over the past few years we can see there is an occurrence of floods at different parts of the world almost every year. The technical advancements in recent years have made it easier to get a solution for these natural disasters. One of such technologies which takes us much closer to the internet is the “Internet of Things”. This paper consists of flood detection and avoidance system using the iot technology. The sensors present in this are used to estimate the water levels, humidity, and temperature and send the real-time data to the cloud and the users can access the data via the mobile app. This model is widely used to alarm the people before a flood occurs and necessary precautions could be taken.

Multi-Disciplinary Opinions Focused on Healthcare Sector for Global Pandemic: COVID-19 (Preprint)

2020 ◽  
Author(s):  
Vinod Kumar Verma
Keyword(s):  
Internet Of Things ◽  
Research Community ◽  
Security And Privacy ◽  
Healthcare Sector ◽  
The Internet ◽  
Thought Process ◽  
Related Information ◽  
Global Pandemic ◽  
The People ◽  
The Internet Of Things

BACKGROUND COVID- 19 pandemics has affected the life of every human being in this world dramatically. The daily routine of the human has been changed to an uncertain extent. Some of the people are affected by the COVID-19, and some of the people are in fear of this epidemic. This has completely changed the thorough process of the people, and now, they are looking for solutions of this pandemic at different levels of the human addressable areas. These areas include medicine, vaccination, precautions, psychology, technology-assisted solutions like information technology, etc. There is a need to think in the direction of technology compliant solutions in the era of COVID-19 pandemic. OBJECTIVE The objective of this paper is to discuss the existing views and focus on the recommendations for the enhancement in the current situation from COVID-19. METHODS Based on the literature, perceptions, challenges, and viewpoints, the following opinions are suggested to the research community for the prevention and elimination of global pandemic COVID-19. The research community irrespective of the discipline focus on the following: 1. The comprehensive thought process for the designing of the internet of things (IoT) based solutions for healthcare applications used in the prevention from COVID-19. 2. Strategies for restricting outbreak of COVID-19 with the emerging trends in Ehealthcare applications. Which should be the optimal strategy to deal with a global pandemic? 3. Explorations on the data analysis as derived from the advanced data mining and warehousing associated with IoT. Besides, cloud-based technologies can be incorporated for the global spread of healthcare-related information to serve the community of different countries in the world. 4. The most adaptable method and technology can be deployed for the development of innovative solutions for COVID-19 related people like smart, patient-centric healthcare information systems. 5. Implementation of smart solutions like wearable technology for mask and PPE along with their disposal can be considered to deal with a global epidemic like COVID-19. This will lead to the manufacturing and incorporation of wearable technologies in the healthcare sector by industries. 6. A Pervasive thought process can be standardized for dealing with global pandemic like COVID-19. In addition, research measures should be considered for the security and privacy challenges of IoT services carrying healthcare-related information. These areas and directions are diverse but, in parallel, the need for healthy bonding and correlation between the people like researchers and scientists irrespective of their discipline. The discipline may vary from medical, engineering, computing, finance, and management, etc. In addition, standard protocols and interoperability measures can be worked out for the exchange of information in the global pandemic situations. RESULTS Recommendations Discussed CONCLUSIONS In this paper, the opinions have been discussed in the multi-disciplinary areas of research like COVID-19 challenges, medicines and vaccines, precautionary measures, technology assistance, and the Internet of Things. These opinions and discussion serve as an integrated platform for researchers and scientists to think about future perspectives to deal with healthcare-related COVID-19 pandemic situation. This includes the original, significant, and visionary automation based ideas, innovations, scientific designs, and applications focusing on Inter-disciplinary technology compliant solutions like IoT, vaccinations, manufacturing, preventive measures, etc. for the improvement of efficiency and reliability of existing healthcare systems. For the future, there is dire need to strengthen the technology not only in the one area but also for the interdisciplinary areas to recover from the pandemic situation rapidly and serve the community.

Sustainable Security for the Internet of Things Using Artificial Intelligence Architectures

2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Experimental Testing ◽  
Cyber Attacks ◽  
Internet Technology ◽  
The Internet ◽  
Business Operations ◽  
Private Data ◽  
The Internet Of Things ◽  
Better Than

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.

scholarly journals Rancang Bangun Jemuran Otomatis Menggunakan Mikrokontroller WEMOS

CAHAYAtech ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Adetya Windiarto Makhmud ◽  
Tutus Praningki ◽  
Ira Luvi Indah
Keyword(s):  
Internet Of Things ◽  
Solar Energy ◽  
Light Intensity ◽  
Weather Conditions ◽  
Daily Activities ◽  
The Internet ◽  
The Right ◽  
The Internet Of Things

Drying clothes is one of the daily activities of people who use solar energy. With these conditions, people are very dependent on weather conditions that are sometimes erratic. One of the right ways is by utilizing technology, namely using an automatic clothesline using a Wemos D1Mini microcontroller, equipped with an LDR sensor that will read light intensity and the DHT11 sensor will read humidity and temperature around the environment. This tool is also based on the Internet of Things which can be accessed from anywhere as long as it is connected to the internet. Keyword: Microcontroller, LDR sensor, DHT11 sensor, Internet of Things.

scholarly journals Acceptance of Smart Electronic Monitoring at Work as a Result of a Privacy Calculus Decision

Informatics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 40
Author(s):  
Evgenia Princi ◽  
Nicole C. Krämer
Keyword(s):  
Electronic Monitoring ◽  
Detection System ◽  
Monitoring Systems ◽  
The Internet ◽  
Privacy Concerns ◽  
User Data ◽  
Privacy Calculus ◽  
System Acceptance ◽  
Emergency Detection ◽  
The Internet Of Things

Smart technology in the area of the Internet of Things (IoT) that extensively gathers user data in order to provide full functioning has become ubiquitous in our everyday life. At the workplace, individual’s privacy is especially threatened by the deployment of smart monitoring technology due to unbalanced power relations. In this work we argue that employees’ acceptance of smart monitoring systems can be predicted based on privacy calculus considerations and trust. Therefore, in an online experiment (N = 661) we examined employees’ acceptance of a smart emergency detection system, depending on the rescue value of the system and whether the system’s tracking is privacy-invading or privacy-preserving. We hypothesized that trust in the employer, perceived benefits and risks serve as predictors of system acceptance. Moreover, the moderating effect of privacy concerns is analyzed.

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

Design and Implementation of Automated Warehouse Monitoring System Based on the Internet of Things

2014 ◽  
Vol 543-547 ◽  
pp. 1099-1102 ◽  
Author(s):  
Zhi Qiang Yao ◽  
Heng Jun Zhu ◽  
Wen He Du
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Humidity Sensor ◽  
The Internet ◽  
Design And Implementation ◽  
Zigbee Technology ◽  
Temperature And Humidity ◽  
The Internet Of Things

Aiming at the lagging for the monitoring of warehouse and lacking the intelligence, an automated warehouse monitoring system is designed using the internet of things, which may be used to monitor the temperature, humidity, and case of fire in the warehouse simultaneously. The temperature and humidity sensor SHT10 is implemented as the detector of the temperature and humidity, the flame sensor R2868 and the ionic smoke transducer HIS-07 are implemented as the detector of smoke and flame to find the fire. These data are sent to the computer in the manager center through Zigbee technology and the computer will process and analyze them. When the fire occurs, this system can extinguish the fire and call the manager or 119 automatically. The experiments have been performed, and it is shown that the performance of system is reliable, which has the practical value.

scholarly journals Agrocompanion: A Smart Farming Approach Based on Iot and Machine Learning

2020 ◽  
Vol 9 (12) ◽  
pp. 254-262
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Random Forest ◽  
Weather Conditions ◽  
The Internet ◽  
Machine Learning Model ◽  
Smart Farming ◽  
Water Tanks ◽  
And Control ◽  
The Internet Of Things

Agriculture is one of the cardinal sectors of the Indian Economy. The proposed system offers a methodology to efficiently monitor and control various attributes that affect crop growth and production. The system also uses machine learning along with the Internet of Things (IoT) to predict the crop yield. Various weather conditions such as temperature, humidity, and soil moisture are monitored in real-time using IoT sensors. IoT is also used to regulate the water level in the water tanks, which helps in reducing the wastage of water resources. A machine learning model is developed to predict the yield of the crop based on parameters taken from these sensors. The model uses Random Forest Regressor and gives an accuracy of 87.5%. Such a system provides a simple and efficient way to maintain and monitor the health of the crop.

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