scholarly journals IoT for Smart Environment Monitoring Based on Python: A Review

2021 ◽  
pp. 57-70
Author(s):  
Saad Hikmat Haji ◽  
Amira B. Sallow
Keyword(s):  
Water Pollution ◽  
Machine Learning ◽  
Internet Of Things ◽  
Environmental Monitoring ◽  
Sensor Technology ◽  
The Internet ◽  
Smart Environment ◽  
Environment Monitoring ◽  
The Internet Of Things

Air pollution, water pollution, and radiation pollution are significant environmental factors that need to be addressed. Proper monitoring is crucial with the goal that by preserving a healthy society, the planet can achieve sustainable development. With advancements in the internet of things (IoT) and the improvement of modern sensors, environmental monitoring has evolved into a smart environment monitoring (SEM) system in recent years. This article aims to have a critical overview of significant contributions and SEM research, which include monitoring the quality of air , water pollution, radiation pollution, and agricultural systems. The review is divided based on the objectives of applying SEM methods, analyzing each objective about the sensors used, machine learning, and classification methods. Moreover, the authors have thoroughly examined how advancements in sensor technology, the Internet of Things, and machine learning methods have made environmental monitoring into a truly smart monitoring system.

scholarly journals The Aquaponic Ecosystem Using IoT and IA Solutions

2022 ◽  
Vol 17 (5) ◽  
pp. 1-15
Author(s):  
Ibtissame Ezzahoui ◽  
Rachida Ait Abdelhouahid ◽  
Khaoula Taji ◽  
Abdelaziz Marzak ◽  
Fadoua Ghanimi
Keyword(s):  
Water Pollution ◽  
Internet Of Things ◽  
Human Evolution ◽  
Performance Measures ◽  
Negative Impact ◽  
The Other ◽  
The Internet ◽  
Smart Environment ◽  
The Internet Of Things

For solving the negative impact of the human evolution in earth, water, pollution and quality of feed. A system of aquaponic is proposed to manage gardening and recover up to 90% of water used for plants. Aquaponic is a system that combines two names: aquaculture which is the farming of fish and hydroponic which is the cultivation of plants (off-soil). On the other hand, the possibility of using the phytotron system. The objective of this solution is to collect performance measures, to control the watering conditions of plants (water level, temperature, humidity, ...) With a cloud support and other possibilities offered by the internet of things (IoT). The paper at hand aim to provide a smart solution integrates the phytotron solution in order to control the first part wish is the hydroponic and the second part concerning the aquaculture in order to offer a smart environment for the cycle of fish’s life.

The Aquaponic Ecosystem Using IoT and IA Solutions

2022 ◽  
Vol 17 (5) ◽  
pp. 0-0
Keyword(s):  
Water Pollution ◽  
Internet Of Things ◽  
Human Evolution ◽  
Performance Measures ◽  
Negative Impact ◽  
The Other ◽  
The Internet ◽  
Smart Environment ◽  
The Internet Of Things

For solving the negative impact of the human evolution in earth, water, pollution and quality of feed. A system of aquaponic is proposed to manage gardening and recover up to 90% of water used for plants. Aquaponic is a system that combines two names: aquaculture which is the farming of fish and hydroponic which is the cultivation of plants (off-soil). On the other hand, the possibility of using the phytotron system. The objective of this solution is to collect performance measures, to control the watering conditions of plants (water level, temperature, humidity, ...) With a cloud support and other possibilities offered by the internet of things (IoT). The paper at hand aim to provide a smart solution integrates the phytotron solution in order to control the first part wish is the hydroponic and the second part concerning the aquaculture in order to offer a smart environment for the cycle of fish’s life.

Applying the Internet of Things into Ecological Environmental Monitoring

2012 ◽  
Vol 198-199 ◽  
pp. 1755-1760 ◽  
Author(s):  
Guo Ping Zhou ◽  
Ya Nan Chen
Keyword(s):  
Internet Of Things ◽  
Environmental Monitoring ◽  
Software Design ◽  
Ecological Environment ◽  
Future Research ◽  
The Internet ◽  
Environment Monitoring ◽  
Carbon Dioxide Gas ◽  
Data Collection And Analysis ◽  
The Internet Of Things

Applying the Internet of Things (IOT) into ecological environmental monitoring is the goal of this paper. There are several advantages of the Internet of Things (IOT) applying in ecological environment monitoring. A hierarchical monitoring system is presented, including system architecture, hardware/software design, information flow and software implementation. In the end, using carbon dioxide gas in the atmosphere for experimental purposes, in data collection and analysis. Experiments showed that this system is capable of monitoring ecologica environment, which orientate the future research of forest ecosystem.

scholarly journals An Agent-Based Approach to Realize Emergent Configurations in the Internet of Things

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1347 ◽  
Author(s):  
Fahed Alkhabbas ◽  
Romina Spalazzese ◽  
Paul Davidsson
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
The Internet ◽  
Daily Lives ◽  
Agent Based ◽  
Design Time ◽  
Underlying Processes ◽  
The Internet Of Things

The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability.

scholarly journals A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 880
Author(s):  
Imran ◽  
Zeba Ghaffar ◽  
Abdullah Alshahrani ◽  
Muhammad Fayaz ◽  
Ahmed Mohammed Alghamdi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quality Of Service ◽  
Internet Of Things ◽  
Software Defined Networking ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Resources Management ◽  
Learning Techniques ◽  
The Internet Of Things

In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of data. One major contribution to the research world is in the form of software-defined networking applications, which aim to deploy rule-based management to control and add intelligence to the network using high-level policies to have integral control of the network without knowing issues related to low-level configurations. Machine learning techniques coupled with software-defined networking can make the networking decision more intelligent and robust. The Internet of Things application has recently adopted virtualization of resources and network control with software-defined networking policies to make the traffic more controlled and maintainable. However, the requirements of software-defined networking and the Internet of Things must be aligned to make the adaptations possible. This paper aims to discuss the possible ways to make software-defined networking enabled Internet of Things application and discusses the challenges solved using the Internet of Things leveraging the software-defined network. We provide a topical survey of the application and impact of software-defined networking on the Internet of things networks. We also study the impact of machine learning techniques applied to software-defined networking and its application perspective. The study is carried out from the different perspectives of software-based Internet of Things networks, including wide-area networks, edge networks, and access networks. Machine learning techniques are presented from the perspective of network resources management, security, classification of traffic, quality of experience, and quality of service prediction. Finally, we discuss challenges and issues in adopting machine learning and software-defined networking for the Internet of Things applications.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

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