Internet of Things (IoT) and Deep Neural Network-Based Intelligent and Conceptual Model for Smart City

Gautam, Kalpna; Puri, Vikram; Tromp, Jolanda G.; Nguyễn, Như Gia; Le, Chung Van

doi:10.1007/978-981-32-9186-7_30

Cited by 6 publications

(4 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the era of faster communication and even faster computational needs, fog computing prevails in the industry with such requirements by processing data closer to the source. Modern advancements such as big data analytics, machine learning, and deep learning are combined with fog for generating data analytics on the fly with adaptive learning [ 31 , 32 , 33 , 34 ]. Leveraging the technology of blockchain to accommodate privacy and security features in the fog layer is proposed in [ 35 , 36 , 37 ].…”

Section: Current State-of-the-artmentioning

confidence: 99%

An Overview of Fog Data Analytics for IoT Applications

Bhatia

Italiya²,

Jadeja

et al. 2022

Sensors

View full text Add to dashboard Cite

With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one of the promising solutions for handling the big data produced by the IoT, which are often security-critical and time-sensitive. Massive IoT data analytics by a fog computing structure is emerging and requires extensive research for more proficient knowledge and smart decisions. Though an advancement in big data analytics is taking place, it does not consider fog data analytics. However, there are many challenges, including heterogeneity, security, accessibility, resource sharing, network communication overhead, the real-time data processing of complex data, etc. This paper explores various research challenges and their solution using the next-generation fog data analytics and IoT networks. We also performed an experimental analysis based on fog computing and cloud architecture. The result shows that fog computing outperforms the cloud in terms of network utilization and latency. Finally, the paper is concluded with future trends.

show abstract

Section: Current State-of-the-artmentioning

confidence: 99%

An Overview of Fog Data Analytics for IoT Applications

Bhatia

Italiya²,

Jadeja

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Reducing system overload and the size of data collected by the sensors requires the use of cryptographic processing algorithms to transmit only the necessary information to the database via wireless communication [120].…”

Section: The Future Directionsmentioning

confidence: 99%

Gas sensing based on organic composite materials: Review of sensor types, progresses and challenges

Nasri

Pétrissans

Fierro

2021

Materials Science in Semiconductor Processing

View full text Add to dashboard Cite

Over the past decade, organic semiconductors and renewable resources have aroused great interest in basic research and practical applications. Composites based on organic materials and materials of biological origin, if not all bio-based, are potentially abundant and partly biodegradable. These materials have demonstrated advantages making them ideally suited for gas-sensing applications. Herein, we present different detection principles of gas sensing, such as electrochemical, resistive, capacitive, and acoustic sensors. Besides, we describe sensing properties and suitable materials to enhance the selectivity, sensitivity and response/recovery time of gas sensors. In addition, an overview of different forms of materials based on renewable resources and inorganic/organic semiconductors, as well as the development of different types of sensors are discussed. Finally, challenges and future directions are examined in order to develop a low-cost microscale sensing technology using composite materials based on renewable resources. We anticipate that chemical engineering, computer science, machine learning and embedded systems can contribute to the development of new sensing materials.

show abstract

“…Electronic mail is the exchanging of digital messages by telecommunication between people using digital devices such as mobile phones, computers, and tablets. Electronic mail first uses in the 1960s and by the mid-1970s had taken the form now recognized as email [21]. Email systems required both the sender and the recipient online to receive the snapshot at the same time.…”

Section: E-mail or Emailmentioning

confidence: 99%

Design and implement a smart system to detect intruders and firing using IOT

Kadhim,

MohammedAmeen

2020

IJECE

View full text Add to dashboard Cite

The security system is essential for occupants' convenience and protection from intruders and fire. Theft and fire are the most important requirement for the security system. The advancement of wireless sensor networks using IOTs increased the features in a security system and play an important role in daily life. In this paper, the proposed system is divided into two units. The first one about security which use to take snapshots by a camera whenever there is fire or intruders in the security zone and mail it to the owner every three seconds by using Arduino configured with MATLAB program. MATLAB program plays the main role to coordinate between sensors and to turn on/off the cameras. The second unit is about controlling the appliances and also the main door by using AVR microcontroller configured by CVAVR software that connected with Bluetooth sensor and controlled by a smartphone by using the implementation software built-up in the smartphone. To arrival of the control unit, the user should send code from the software implementation to the framework that use to turn on /off the devices or open/close the door. This proposed system is designed and implemented in details in this paper.

show abstract

Internet of Things (IoT) and Deep Neural Network-Based Intelligent and Conceptual Model for Smart City

Cited by 6 publications

References 10 publications

An Overview of Fog Data Analytics for IoT Applications

An Overview of Fog Data Analytics for IoT Applications

Gas sensing based on organic composite materials: Review of sensor types, progresses and challenges

Design and implement a smart system to detect intruders and firing using IOT

Contact Info

Product

Resources

About