Application of Hyperspectral Image Unmixing for Internet of Things

2020 ◽  
pp. 249-260
Author(s):  
Menna M. Elkholy ◽  
Marwa Mostafa ◽  
Hala M. Ebeid ◽  
Mohamed F. Tolba
Keyword(s):  
Internet Of Things ◽  
Hyperspectral Image

scholarly journals Encoding Spectral-Spatial Features for Hyperspectral Image Classification in the Satellite Internet of Things System

2021 ◽  
Vol 13 (18) ◽  
pp. 3561
Author(s):  
Ning Lv ◽  
Zhen Han ◽  
Chen Chen ◽  
Yijia Feng ◽  
Tao Su ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Land Cover ◽  
Image Classification ◽  
Large Scale ◽  
High Efficiency ◽  
Hyperspectral Image ◽  
Remote Sensing Data ◽  
Hyperspectral Images ◽  
Hyperspectral Image Classification ◽  
Spatial Features

Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.

scholarly journals On Using Artificial Intelligence and the Internet of Things for Crop Disease Detection: A Contemporary Survey

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 9
Author(s):  
Houda Orchi ◽  
Mohamed Sadik ◽  
Mohammed Khaldoun
Keyword(s):  
Internet Of Things ◽  
Plant Pathogens ◽  
Agricultural Sector ◽  
Hyperspectral Image ◽  
Future Perspective ◽  
The Internet ◽  
Disease Detection ◽  
Disease Identification ◽  
Crop Disease ◽  
The Internet Of Things

The agricultural sector remains a key contributor to the Moroccan economy, representing about 15% of gross domestic product (GDP). Disease attacks are constant threats to agriculture and cause heavy losses in the country’s economy. Therefore, early detection can mitigate the severity of diseases and protect crops. However, manual disease identification is both time-consuming and error prone, and requires a thorough knowledge of plant pathogens. Instead, automated methods save both time and effort. This paper presents a contemporary overview of research undertaken over the past decade in the field of disease identification of different crops using machine learning, deep learning, image processing techniques, the Internet of Things, and hyperspectral image analysis. Additionally, a comparative study of several techniques applied to crop disease detection was carried out. Furthermore, this paper discusses the different challenges to be overcome and possible solutions. Then, several suggestions to address these challenges are provided. Finally, this research provides a future perspective that promises to be a highly useful and valuable resource for researchers working in the field of crop disease detection.

scholarly journals Hyperspectral Image Processing in Internet of Things model using Clustering Algorithm

2021 ◽  
Vol 3 (2) ◽  
pp. 163-175
Author(s):  
Bindhu V ◽  
Ranganathan G
Keyword(s):  
Internet Of Things ◽  
Clustering Algorithm ◽  
Hyperspectral Image ◽  
Clustering Algorithms ◽  
Subspace Clustering ◽  
Observation System ◽  
Sorting Algorithm ◽  
Post Process ◽  
Hyper Spectral ◽  
Process Strategy

With the advent of technology, several domains have b on Internet of Things (IoT). The hyper spectral sensors present in earth observation system sends hyper spectral images (HSIs) to the cloud for further processing. Artificial intelligence (AI) models are used to analyse data in edge servers, resulting in a faster response time and reduced cost. Hyperspectral images and other high-dimensional image data may be analysed by using a core AI model called subspace clustering. The existing subspace clustering algorithms are easily affected by noise since they are constructed based on a single model. The representation coefficient matrix connectivity and sparsity is hardly balanced. In this paper, connectivity and sparsity factors are considered while proposing the subspace clustering algorithm with post-process strategy. A non-dominated sorting algorithm is used for that selection of close neighbours that are defined as neighbours with high coefficient and common neighbours. Further, pruning of useless, incorrect or reserved connections based on the coefficients between the close and sample neighbours are performed. Lastly, inter and intra subspace connections are reserved by the post-process strategy. In the field of IoT and image recognition, the conventional techniques are compared with the proposed post-processing strategies to verify its effectiveness and universality. The clustering accuracy may be improved in the IoT environment while processing the noise data using the proposed strategy as observed in the experimental results.

Multimedia system and database simulation based on internet of things and cloud service platform

2020 ◽  
pp. 1-12
Author(s):  
Zhang Caiqian ◽  
Zhang Xincheng
Keyword(s):  
Internet Of Things ◽  
Cloud Service ◽  
Multimedia System ◽  
The Internet ◽  
Multimedia Database ◽  
Cloud Platform ◽  
Service Platform ◽  
Device Management ◽  
Cloud Service Platform ◽  
The Internet Of Things

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.

A Survey on Internet of Things : Applications and Layered Wise Security Issues

2019 ◽  
pp. 171-180
Author(s):  
Uppuluri Sirisha ◽  
G. Lakshme Eswari
Keyword(s):  
Quality Of Life ◽  
Internet Of Things ◽  
Security And Privacy ◽  
Global Network ◽  
Business Growth ◽  
Paper Briefly ◽  
Smart Meters ◽  
Security Issues ◽  
Data Points

This paper briefly introduces Internet of Things(IOT) as a intellectual connectivity among the physical objects or devices which are gaining massive increase in the fields like efficiency, quality of life and business growth. IOT is a global network which is interconnecting around 46 million smart meters in U.S. alone with 1.1 billion data points per day[1]. The total installation base of IOT connecting devices would increase to 75.44 billion globally by 2025 with a increase in growth in business, productivity, government efficiency, lifestyle, etc., This paper familiarizes the serious concern such as effective security and privacy to ensure exact and accurate confidentiality, integrity, authentication access control among the devices.

Comprehensive Study of Blockchain Technology - Architecture, Consensus and Future Trends

2020 ◽  
pp. 319-325
Author(s):  
Shreya Joshi ◽  
Ms Bhavyaa ◽  
Suhani Gupta ◽  
Lalita Luthra
Keyword(s):  
Internet Of Things ◽  
Product Management ◽  
Future Trends ◽  
Deep Dive ◽  
Record Keeping ◽  
Blockchain Technology ◽  
Healthcare Product ◽  
Core Technology ◽  
Technical Challenges ◽  
Comprehensive Study

Blockchain is considered to be a disruptive core technology. Although many researchers have realized the importance of blockchain, but the research of it is still emerging. It is the record-keeping technology behind bitcoin and is one of the hottest and fastest growing skills in the IT sector today. It serves as an immutable ledger which allows transactions to take place in a decentralized man Blockchain-based applications are rising up, covering numerous fields including finance, healthcare, product management, Internet of Things (IoT), and many more. However, there are still some challenges of blockchain technology such as scalability and security problems which need to be overcome. This paper comprises of a comprehensive study of Blockchain technology. We have included here a deep dive into how blockchains work, its architecture, consensus and various applications. Furthermore, technical challenges are briefly listed.

PENGGUNAAN INTERNET OF THINGS DALAM PEMASARAN PRODUK PERTANIAN

2018 ◽  
Vol 3 (2) ◽  
pp. 74
Author(s):  
Helina Apriyani ◽  
Sismadi Sismadi ◽  
Sefrika Sefrika
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Electronic Devices ◽  
Agricultural Products ◽  
Main Concept ◽  
Farmers Market ◽  
Incremental Method ◽  
Sales Process ◽  
Internet Connections

AbstrakInternet of things (IoT) adalah sebuah konsep yang menghubungkan komputer dan perangkat elektronik melalui internet dan dapat dikendalikan dari jarak jauh. Konsep terpenting dalam Internet of things (Iot) adalah modul sistem informasi, koneksi internet dan penyimpanan datanya dalam cloud computing. Konsep ini memiliki manfaat besar dalam perkembangan usaha dan kelangsungan bisnis perusahaan dimana hampir semua bidang menggunakan IoT untuk dapat bersaing di pasaran. Indonesia merupakan sebuah negara yang dianugerahi kekayaan alam yang melimpah ruah. Salah satu komoditi unggulan adalah produk pertanian. Penelitian ini bertujuan untuk membantu para petani dalam memasarkan produknya melalui e-commerce dengan menggunakan konsep Internet of things IoT. Metode penelitian dengan menggunakan metode incremental.  Incremental digunakan untuk mendesai produk, kemudian  diimplementasikan, dan diuji secara bertahap (setiap modul akan ditambahkan bertahap) hingga produk selesai. Hasil penelitian ini digunakan untuk membantu petani di Kabupaten Bogor untuk mendistribusikan penjualannya secara luas, meningkatkan revenue dan memutus rantai panjang proses penjualan. Kata kunci— sistem penjualan, incremental, Internet of Things (IoT), produk pertanian, Kabupaten Bogor Abstract Internet of things (IoT) is a concept that connects computers and electronic devices via the internet and can be controlled remotely. The main concept in Internet of things (IoT) is information systems, internet connections and data storage in cloud computing. This concept has great benefits in the efforts and efforts used to use IoT to be able to compete in the market. Indonesia is a country that is blessed with abundant natural resources. One of the leading commodities is agricultural products. This study aims to help farmers market their products through e-commerce using the IoT Internet of things concept. Research method using incremental method. Incremental to design the product, then implemented, and gradually delay (each module will be added gradually) until the product is finished. The results of this study are to help farmers in Bogor Regency to distribute sales widely, increase revenue and break the sales process. Keywords—sales system, incremental, Internet of Things (IoT), agricultural products, Kabupaten Bogor

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