Internet of Things and Its Applications: An Overview

Polepaka, Sanjeeva; Das, M. Swami; Kumar, Rituraj

doi:10.1007/978-981-15-3125-5_8

Cited by 4 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ANN is capable of handling large amounts of non-linear data interpolated. Another definition of an Artificial Neural Network is the paradigm of information processing inspired by the biological nervous system, such as the process of information in the human brain [13].…”

Section: Monitoring Based On Internet Of Thingsmentioning

confidence: 99%

“…The researchers have developed many design heuristics for the hidden layers; these different heuristics help the network behave the way they want it. Another sense of Artificial Neural networks was the paradigm of information processing inspired by the biological nervous system, such as the process of information in the human brain [13].…”

Section: Classifying Using Artificial Neural Networkmentioning

confidence: 99%

“…The requirement of fresh milk that can be consumed successfully goes through a causal test following SNI standards. The benefits of fresh milk can prevent various diseases and help relieve brain performance [13]. One of the largest dairy cattle businesses in East Java is located in Pujon Subdistrict, which is included in the Malang regency.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An analysis and design of fresh milk smart grading system based on internet of things

Habsari

Udin

Arkeman

2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

The grading of fresh milk affects the quality classification in the dairy industry. This study aims to analyze and design a smart grading system using machine learning models to classify the grade of fresh milk. Business process analysis helped understand the capturing steps as the main elements, such as the smart grading system. The result of the requirement analysis showed how smart the grading system involved stakeholders. The machine learning model can help the Internet of Things system classify goods or services. Artificial Neural Network and K-means were designed to classify and group indicators of fresh milk quality. The variables used in this study consisted of pH, temperature, odour, turbidity, colour, fat, and taste values. The data were taken from the upstream dairy industry SAE Pujon. The classification result of fresh milk grades using ANN consisted of three low, medium, and high grades. The accuracy value of the classification obtained is 98.74%. The attributes used for grouping were temperature and colour. The best clusterization that used K-Means is the third cluster. Based on the data analysis, the smart grading system made users save time knowing the grade of fresh milk easier.

show abstract

Section: Monitoring Based On Internet Of Thingsmentioning

confidence: 99%

Section: Classifying Using Artificial Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An analysis and design of fresh milk smart grading system based on internet of things

Habsari

Udin

Arkeman

2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…The IT service is available to connect with this 'smart object' by the internet, and they're asking for the status and information related to it, taking into account security and privacy concerns. [3].…”

Section: Introductionmentioning

confidence: 99%

Internet of Things for Smart Future Science Laboratory in Middle School: A Literature Review

Kusuma¹,

Ikhsan²,

Hujatulatif³

et al. 2021

Proceedings of the 6th Asia-Pacific Education and Science Conference, AECon 2020, 19-20 December 2020, Purwokerto, Indonesia

View full text Add to dashboard Cite

Technology is urgently needed in the era of education 4.0 when technology and human are straight to bring through the new odds of multimedia and technology. The 21st century education in the digital literacy era requires students to able for using the multimedia technology. The recently of the new technology that are start to be widely is The Internet of Things (IoT). The technology concept that can expand using of internet connectivity by automatically connecting us to objects around us called IoT. IoT connecting us by censoring object. The IoT has commenced to broadly used and discussed in any fields such as education field, health field, architecture field, etc. Smart homes, smart cities, smart rooms, smart libraries, etc. also take advantage of IoT technology to facilitate their work. The reasearch using a literature review method. The aims of this paper is to see the benefits and the framework of IoT technology when it applied to a smart laboratory in middle school level.

show abstract

IoT and Machine Learning Based Anomaly Detection in WSN for a Smart Greenhouse

Joaquim

Kamble

Misra

et al. 2022

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Agriculture is the most crucial sector which raises the economy of every country; several techniques have been developed to control and monitor the environment in which a particular crop is growing. Famers need efficient support in terms of monitoring the temperature, the humidity, the water supply etc. However, the measurements provided by a wireless sensor network within a smart greenhouse are an essential aspect to take into consideration when it comes to evaluating the performance of sensor nodes used for controlling and monitoring the climatic condition (temperature, humidity, water supply, etc.). Therefore, this paper proposes a machine learning-based anomaly detection approach with the help of the DBSCAN algorithm of clustering to determine whether an unusual event has been found in the data. This approach allows farmers to ensure the reliability of the network. In this paper, we presented the description of the DBSCAN algorithm; we used an existing dataset that incorporates information about rose cultivation. With the used dataset, we introduced some noise, and we used MATLAB and Python to analyse and predict whether the introduced data is noise or not with DBSCAN. The performance of the algorithm after performing the prediction is 100% for two chosen features of the dataset and 75.4% for five features of the dataset in terms of precision. Keywords  Anomaly detection  Wireless sensor network  Smart greenhouse This is a preview of subscription content, access via your institution.

show abstract

Internet of Things and Its Applications: An Overview

Cited by 4 publications

References 14 publications

An analysis and design of fresh milk smart grading system based on internet of things

An analysis and design of fresh milk smart grading system based on internet of things

Internet of Things for Smart Future Science Laboratory in Middle School: A Literature Review

IoT and Machine Learning Based Anomaly Detection in WSN for a Smart Greenhouse

Contact Info

Product

Resources

About