Smart Room Menggunakan Internet Of Things Untuk Efisiensi Biaya dan Keamanan Ruangan

2019 ◽  
Author(s):  
Robby Yuli Endra
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Smart Room

Revolus industry 4.0 tidak dapat dielakan, oleh sebab itu kitaharus mempersiapkan diri semaksimal mungkin. Beberapateknologi mutakhir di IR 4.0 contohnya Artificial Intelligence(kecerdasaan buatan), Big data dan Internet of Things. Buku Smart Room dengan menggunakan Internet of Things (IoT)buku yang membahas konsep otomatisasi ruangan denganmenggunakan sensor-sensor serta mikrokontroler Arduino sertapenggunaan Internet. Buku ini merupakan buku referensi hasildari penelitian penulis. Pada buku ini juga dijelaskan tahap-tahappembuatan prototype Smart Room dari tools-tools yangdigunakan, pengkodingan serta konsep dan arsitektur SmartRoom.Diharapkan buku referensi ini dapat bermanfaat di duniaakademis, sebagai bahan referensi ataupun bahan diskusi untukbelajar dan mengembang konsep Internet of Things (IoT) yanglebih luas lagi.Ucapan terima kasih tak lupa kami sampaikan kepada semua pihakyang telah membantu dalam penerbitan buku referensi ini. Tidakada gading yang tak retak, buku ini jauh dari kata sempurna olehsebab kami menerima masukan untuk penyempurnaan buku ini.

Balancing Exploration and Exploitation Through Customer Development Model

2021 ◽  
pp. 839-852
Author(s):  
Krishna Raj Bhandari
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Best Practices ◽  
Industry 4.0 ◽  
Development Model ◽  
Exploration And Exploitation ◽  
Customer Development

Balancing exploration and exploitation in entrepreneurial ventures enabled by Industry 4.0 has not been the focus of the existing literature. It is because the phenomenon is emerging and the focus has been to use practitioners' best practices in studying such phenomenon. In this chapter, the author combines the literature in balancing exploration and exploitation with the practitioners' best practices such as customer development model and lean startup. The author proposes that the existing models are good in principle but in order to really solve the problem in such an uncertain environment driven by big data, cloud computing, internet of things (IoT), and artificial intelligence, managers need to embed optimization algorithms in their decision making.

Emerging Auditing Perspectives in the Age of the Fourth Industrial Revolution

2021 ◽  
pp. 999-1014
Author(s):  
Mahmut Sami Ozturk
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Methodological Approach ◽  
The Internet ◽  
Fourth Industrial Revolution ◽  
The Internet Of Things

The purpose of this chapter is to investigate the role of audit activities and auditors in Industry 4.0. The preferred methodological approach in the study is a general analysis of auditing in Industry 4.0 in the form of a literature review. According to the purpose of the study, the effect and role of auditing big data, the internet of things, the cloud, artificial intelligence, and other components in Industry 4.0 are investigated. Furthermore, auditing activities that can be implemented in Industry 4.0 are presented as suggestions in the study. The study explains the role of auditing as a whole in Industry 4.0 as a consequence of examining audit activities for each component in Industry 4.0.

Emerging Auditing Perspectives in the Age of the Fourth Industrial Revolution

2019 ◽  
pp. 172-187
Author(s):  
Mahmut Sami Ozturk
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Methodological Approach ◽  
The Internet ◽  
Fourth Industrial Revolution ◽  
The Internet Of Things

The purpose of this chapter is to investigate the role of audit activities and auditors in Industry 4.0. The preferred methodological approach in the study is a general analysis of auditing in Industry 4.0 in the form of a literature review. According to the purpose of the study, the effect and role of auditing big data, the internet of things, the cloud, artificial intelligence, and other components in Industry 4.0 are investigated. Furthermore, auditing activities that can be implemented in Industry 4.0 are presented as suggestions in the study. The study explains the role of auditing as a whole in Industry 4.0 as a consequence of examining audit activities for each component in Industry 4.0.

scholarly journals Sustainable Industry 4.0 Wireless Networks, Machine Learning Algorithms, and Internet of Things-based Real-Time Production Logistics in Digital Twin-driven Smart Manufacturing

2021 ◽  
Vol 129 ◽  
pp. 04003
Author(s):  
Elvira Nica ◽  
Gheorghe H. Popescu ◽  
George Lăzăroiu
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Real Time ◽  
Industry 4.0 ◽  
Production Systems ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Cyber Physical Production Systems

Research background: The aim of this paper is to synthesize and analyze existing evidence on artificial intelligence-based decision-making algorithms, industrial big data, and Internet of Things sensing networks in digital twin-driven smart manufacturing. Purpose of the article: Using and replicating data from Altair, Catapult, Deloitte, DHL, GAVS, PwC, and ZDNet we performed analyses and made estimates regarding cyber-physical system-based real-time monitoring, product decision-making information systems, and artificial intelligence data-driven Internet of Things systems in digital twin-based cyber-physical production systems. Methods: From the completed surveys, we calculated descriptive statistics of compiled data when appropriate. The data was weighted in a multistep process that accounts for multiple stages of sampling and nonresponse that occur at different points in the survey process. The precision of the online polls was measured using a Bayesian credibility interval. To ensure high-quality data, data quality checks were performed to identify any respondents showing clear patterns of satisficing. Test data was populated and analyzed in SPSS to ensure the logic and randomizations were working as intended before launching the survey. An Internet-based survey software program was utilized for the delivery and collection of responses. The sample weighting was accomplished using an iterative proportional fitting process that simultaneously balanced the distributions of all variables. The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau’s American Community Survey to reflect reliably and accurately the demographic composition of the United States. Confirmatory factor analysis was employed to test for the reliability and validity of measurement instruments. Findings & Value added: The way Internet of Things-based decision support systems, artificial intelligence-driven big data analytics, and robotic wireless sensor networks configure digital twin-driven smart manufacturing and cyber-physical production systems in sustainable Industry 4.0.

Balancing Exploration and Exploitation Through Customer Development Model

2018 ◽  
pp. 147-160 ◽  
Author(s):  
Krishna Raj Bhandari
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Best Practices ◽  
Industry 4.0 ◽  
Development Model ◽  
Exploration And Exploitation ◽  
Customer Development

Balancing exploration and exploitation in entrepreneurial ventures enabled by Industry 4.0 has not been the focus of the existing literature. It is because the phenomenon is emerging and the focus has been to use practitioners' best practices in studying such phenomenon. In this chapter, the author combines the literature in balancing exploration and exploitation with the practitioners' best practices such as customer development model and lean startup. The author proposes that the existing models are good in principle but in order to really solve the problem in such an uncertain environment driven by big data, cloud computing, internet of things (IoT), and artificial intelligence, managers need to embed optimization algorithms in their decision making.

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