scholarly journals Utilizing the Internet of Things (IoT) to Develop a Remotely Monitored Autonomous Floodgate for Water Management and Control

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 502 ◽  
Author(s):  
Sami Salama Hussen Hajjaj ◽  
Mohamed Thariq Hameed Sultan ◽  
Muhammad Hafizuddin Moktar ◽  
Seng Hua Lee

In recent years, floods have increased in frequency and intensity, causing tremendous hardship. In badly affected regions, mostly the rural areas, Weir-type floodgates are the only measure against floods. However, these manually operated gates are numerous and scattered over vast areas. This makes flood mitigation efforts very challenging, which causes severe devastation. Current solutions to automate the floodgates are expensive, black-boxed, and focused on individual gates. In this paper, we present a Centralized Flood Monitoring and Coordination System developed through the Internet of Things (IoT) and other open-source technologies. For this work, we developed a working prototype of an autonomous floodgate that opens/closes according to the level of water. We also developed the required program to allow the gate controller to publish its data through the IoT gateway to the cloud. The data was then captured and viewed on a number of IoT clients, both for individuals and groups of floodgates, in real time. The developed system proved successful as the autonomous gates were monitored remotely through the established IoT framework, with room for future development and improvement. This paper serves as a proof of concept and a preparation for real, on-site implementation of the IoT-floodgates.

Author(s):  
Konstantinos Kotis ◽  
Artem Katasonov

Internet of Things should be able to integrate an extremely large amount of distributed and heterogeneous entities. To tackle heterogeneity, these entities will need to be consistently and formally represented and managed (registered, aligned, composed and queried) trough suitable abstraction technologies. Two distinct types of these entities are a) sensing/actuating devices that observe some features of interest or act on some other entities (call it ‘smart entities’), and b) applications that utilize the data sensed from or sent to the smart entities (call it ‘control entities’). The aim of this paper is to present the Semantic Smart Gateway Framework for supporting semantic interoperability between these types of heterogeneous IoT entities. More specifically, the paper describes an ontology as the key technology for the abstraction and semantic registration of these entities, towards supporting their automated deployment. The paper also described the alignment of IoT entities and of their exchanged messages. More important, the paper presents a use case scenario and a proof-of-concept implementation.


2021 ◽  
Author(s):  
Jehad Ali ◽  
Byeong-hee Roh

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides an architecture with a global view of the underlying network and manages the E2E heterogeneous networks with AI learning.


Author(s):  
Jathan Sadowski ◽  
Frank Pasquale

There is a certain allure to the idea that cities allow a person to both feel at home and like a stranger in the same place. That one can know the streets and shops, avenues and alleys, while also going days without being recognized. But as elites fill cities with “smart” technologies — turning them into platforms for the “Internet of Things” (IoT): sensors and computation embedded within physical objects that then connect, communicate, and/or transmit information with or between each other through the Internet — there is little escape from a seamless web of surveillance and power. This paper will outline a social theory of the “smart city” by developing our Deleuzian concept of the “spectrum of control.” We present two illustrative examples: biometric surveillance as a form of monitoring, and automated policing as a particularly brutal and exacting form of manipulation. We conclude by offering normative guidelines for governance of the pervasive surveillance and control mechanisms that constitute an emerging critical infrastructure of the “smart city.”


2020 ◽  
Author(s):  
Tanweer Alam ◽  
Baha Rababah ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 27
Author(s):  
Franco Cicirelli ◽  
Antonio Guerrieri ◽  
Andrea Vinci

The Internet of Things (IoT) and related technologies are promising in terms of realizing pervasive and smart applications, which, in turn, have the potential to improve the quality of life of people living in a connected world [...]


Author(s):  
М.А. Держо ◽  
М.М. Лаврентьев ◽  
А.В. Шафаренко

В данной работе обсуждаются фундаментальные вопросы разработки программ магистратуры в области Интернета вещей (Internet of Things — IoT). Мы кратко сравниваем предложения Сколтеха и Стэнфорда и утверждаем, что наиболее гибкое решение достигается посредством вводного блока и четырех параллельных потоков учебных курсов: обработка сигналов и управление, обучение машин и искусственный интеллект (ИИ), программирование и схемотехника платформ с применением микроконтроллеров, и, наконец, сети и кибербезопасность. Вводный блок предполагается оснастить достаточным количеством предметов по выбору, чтобы поступающие выпускники бакалавриата из областей прикладной математики, информационных технологий и электроники/телекоммуникаций могли приобрести необходимые знания для освоения потоковых курсов. Мы утверждаем, что еще одним необходимым отличием программы IoT должен явиться междисциплинарный групповой дипломный проект значительного объема, также основанный на потоковых курсах. This paper discusses the fundamentals of postgraduate curriculum development for the area of the Internet of Things (IoT). We provide a brief contrasting analysis of Skoltech and Stanford Masters programs and argue that the most flexible way forward is via the introduction of a leveling-off, elective introductory stage, and four parallel course streams: signal processing and control; Artificial Intelligence (AI), and machine learning; microcontroller systems design; and networks and cyber security. The leveling-off stage is meant to provide sufficient electives for graduates of applied math, Information Technologies (IT), or electronics/telecom degrees to learn the necessary fundamentals for the stream modules. We argue that another distinguishing feature of an IoT masters program is a large project drawing on the stream modules and requiring a multidisciplinary, team development effort.


2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Yunyan Chang ◽  
Jian Xu ◽  
Kayhan Zrar Ghafoor

In all the smart applications, evolution of the Internet of Things (IOT) is utilized as a complete matured technology and in the future internet generations, established itself. Blockchain is also the blooming technique like Internet of things in which the distributed ledger which enhances the security contained in the each node of the block-chain. In the block-chain network, any fault transaction is not done by the illegal users. The block-chain is combined with the Internet of Things for the improvement of real time application performance. IOT based smart water management system is designed in this paper for the agriculture which ensures the effectiveness of the agriculture water management. The remote monitoring with the IOT is used for this purpose. By linking with 2D modelling, the control and management of the agriculture water were performed. Finally, a system is implemented for the agriculture water management through the real time data collection. The obtained result shows the data that updates the water monitoring interface with the varying number of hours. The IoT technology and remote monitoring technology is utilized to the existing water management infrastructure. For water resources management and water supply, this is the very efficient technology.


Author(s):  
Baha Rababah ◽  
Tanweer Alam ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


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