Week 4 Research Paper: Big Data and the Internet of Things

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Word Count: 1,265 BigDataandtheInternetofThings-week-4ResearchPaper.docx

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Big Data and IoT

Big Data and the Internet of Things

Name: Srilakshmi Keerthy Bandi

Course: Data Science & Big Data Analysis

Instructor: Dr Sethuraman Kuruvimalai

Date: 05.29.2021

Introduction

The way devices are connected using sensors with the help of IoT. The internet monitors the connected devices. However, there is a rapid growth of data produced by IoT due to the large-scale development of cloud computing applications. This ever-increasing data needs a solution to help manage the rapid growth of data

(Babiceanu Seker, 2016). The key to rapidly growing information is big data which is regards as the future data dream. Big data enables one to store unlimited data amounts in a well-secured manner. Therefore, combining big data and the internet of things sets the stage for a technical revolution for the coming generations. The internet of something, being a network of physical devices implanted with software, electronics, and sensors, allows devices to exchange data (Babiceanu Seker, 2016). Ample data storage has two primary necessities: it can handle substantial data quantities while continuously balancing to keep up with the expansion and provide out- put/input operations per second required for data delivery to analytic tools.

Evaluation that aims at making conclusions about the information. Data analytics is applied in various industries to enhance better decision-making in businesses and the verification or disapproval of existing theories or models in science (Tao et al., 2018). The internet of things big data is very crucial in optimized decision-making. The internet of things has made human life easier by enabling human beings to control any device. Various IoT applications such as transportation, manufacturing, smart homes, and consumer goods like smartphones and wearables are available (Tao et al., 2018). IoT is the network of devices consisting of software, actuators, electronics, sensors, and connectivity that enables these devices to connect, interact, and exchange data (Tao et al., 2018). IoT has been to control devices, gather in- formation, disseminate information collected, and transfer the data for analysis and prescription or prediction of solutions for the existing problems.

Benefits of Big Data Analytics for Manufacturing IoT

Big data and the internet of things have various benefits in applications. I discussed some of the services and applications of big data and the internet of items

below. Real-time monitoring is one benefit and application of big data and IoT. Big data collected through connected devices has its application in real-time operations such as tracking physical activities (monitoring movements, counting steps), measuring temperature in the office or at home, etc. (Dai et al. 2020). Real-time mon-

itoring has most of its applications in the healthcare sector, where it is applied in measuring blood pressure, taking heart rate, measuring blood sugar level. Real-time monitoring is also involved in manufacturing in controlling production machinery and agriculture in monitoring plants and cattle.

Also applied Big data and IoT Technology in data analysis. Processing the internet of things-generated data creates an opportunity for one to go beyond monitoring. It enables one to obtain valuable insights into the data, like identifying trends and tendencies, revealing unseen patterns, and finding hidden correlations and informa- tion (Dai et al. 2020). Another benefit of big data and the internet of things is a process control and optimization. Technology enables one to reveal non-trivial issues that affect optimization processes and device or machine performance (Dai et al. 2020). Also applied Big data and the internet of things technology in traffic manage- ment. Can use Big data and IoT technology to track traffic load, determine various times and dates to work traffic optimization recommendations, for instance, in- crease the number of buses and trains, determine profitability, etc.

Applied Big data and IoT technology in the retail sector, such as informing supermarket personnel on when to refill supermarket shelves with merchandise. Used Big data and IoT sensor data in agriculture to water plants and animals (Dai et al. 2020). can use Data collected by big data and IoT technology to identify potentially dan- gerous conditions and predict risks proactively. For instance, in the healthcare sector, this data can be used to monitor the state of patients and identify hazards such as heart attacks, diabetes, and timely measures (Dai et al. 2020). can also use the data can also be used in manufacturing to predict equipment failure.

Challenges of Big Data Analytics for Manufacturing IoT

There is no use of enormous data volumes unless processed to obtain something valuable. These are mainly because large data volumes are characterized by chal- lenges such as connectivity, data collection, data processing, and data storage (Dai et al., 2020). Data reliability is one of the most significant challenges of big

data analytics for manufacturing the internet of things.

Big data can never be 100% accurate, thus posing a considerable challenge when analyzing the data. The sensors must be functioning adequately to ensure quality data generation and analysis. Data storage is also another challenge big data analytics for manufacturing the internet of things technology faces (Dai et al. 2020).

This technology generates terabytes of data that is hard to store. It is also quite challenging to choose which data to keep and which one to discard.

Big data analytics for manufacturing the internet of things technology also faces a challenge of analysis depth. With the vast volume of data associated with tech-

nology, it is pretty challenging to determine the level of analysis that will bring more value (Dai et al., 2020). This is because not all data generated is essential, and one must determine which data to store and which one to discard. Another challenge this technology faces is security. How secure is the data generated by this technolo- gy, particularly from cybersecurity attacks? Cyber attackers can access data devices and the central data storage point and cause serious cybercrime data. And big data technology has few security specialists with relevant experience, thus posing security risks to the data generated (Dai et al. 2020). Other challenges include data acqui- sition like data transmission and representation, data analytics like data-efficient data mining, spatial and temporal data correlation, etc., and challenges in data pre- processing and storage like redundancy reduction, data integration, data compression, etc.

Conclusion

Technological advancements in the information and communication industry have fostered the evolution of intelligent data-driven manufacturing from the com-

puter-aided manufacturing industry. Data analytics enables massive data manufacturing that in turn extracts large business values. However, this has also result-

ed in research challenges because of heterogeneous data, real-time manufacturing data velocity, and enormous data volume. Big data analytics for manufactur-

ing the internet of things technology has numerous benefits, as outlined above. Among them include real-time monitoring, data analysis, processes control, and opti- mization, in manufacturing where it is used to predict machine failure, etc. on the contrary, big data analytics for manufacturing the internet of things technology has challenges such as data acquisition like difficulty in data transmission and representation, data analytics like data-efficient data mining, spatial and temporal data cor- relation, etc., and challenges in data pre-processing and storage like redundancy reduction, data integration, data compression, etc.

References

Babiceanu, R. F., & Seker, R. (2016). Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future out-

look. Computers in Industry, 81, 128-137. Dai, H. N., Wang, H., Xu, G., Wan, J., & Imran, M. (2020). Big data analytics for manufacturing internet of things: op-

portunities, challenges and enabling technologies. Enterprise Information Systems, 14(9-10), 1279-1303. Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-

driven smart manufacturing. Journal of Manufacturing Systems, 48, 157-169.

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Big Data and IoT

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Big IoT data analytics

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Big Data and the Internet of Things

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Big Data and Internet of Things

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Data Science & Big Data Analysis

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Data Science & Big Data Analysis

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Benefits of Big Data Analytics for Manufacturing IoT

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Benefits of Big Data Analytics for Manufacturing IoT

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Big data and the internet of things have various benefits in applications.

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Big Data and Internet of Things

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(Dai et al.

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Dai et al

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Challenges of Big Data Analytics for Manufacturing IoT

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Challenges of Big Data Analytics for Manufacturing IoT

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Data reliability is one of the most significant challenges of big data analytics for manufac- turing the internet of things.

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One of the significant challenges that are associated with Big Data Analytics for Manufac- turing Internet of Things is the challenge of data transmission

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Data storage is also another challenge big data analytics for manufacturing the internet of things technology faces (Dai et al.

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Data storage is another significant challenge associated with big data analytics for the manufacturing of the internet of things

Student paper 67%

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erau 100%

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Big data analytics for manufacturing the internet of things technology also faces a chal- lenge of analysis depth.

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BIG DATA ANALYTICS FOR MANUFACTURING INTERNET OF THINGS

Student paper

Technological advancements in the information and communication industry have fos- tered the evolution of intelligent data-driven manufacturing from the computer-aided manufacturing industry.

Original source

Technology advancements in recent years have triggered the evolution of computer-aided manufacturing industry to smart data-driven manufacturing

Student paper

Data analytics enables massive data manufacturing that in turn extracts large business values.

Original source

In data analytics, massive data manufacturing involves the extraction of tremendous busi- ness values

Student paper

Big data analytics for manufacturing the internet of things technology has numerous ben- efits, as outlined above.

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Big data analytics for manufacturing internet things has several benefits

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F., & Seker, R.

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F., & Seker, R

Student paper

Big Data and virtualization for manufacturing cyber-physical systems:

Original source

"Big Data and virtualization for manufacturing cyber-physical systems

Student paper

A survey of the current status and future outlook. Computers in Industry, 81, 128-137.

Original source

A survey of the current status and future outlook Computers in Industry, 81, 128-137

Student paper

N., Wang, H., Xu, G., Wan, J., & Imran, M.

Original source

N., Wang, H., Xu, G., Wan, J., & Imran, M

Student paper

Big data analytics for manufacturing internet of things: opportunities, challenges and en- abling technologies.

Original source

BIG DATA ANALYTICS FOR MANUFACTURING INTERNET OF THINGS opportunities, chal- lenges, and enabling technologies

Student paper 100%

Student paper

Enterprise Information Systems, 14(9-10), 1279-1303.

Original source

Enterprise Information Systems, 14(9-10), 1279–1303

Student paper

Tao, F., Qi, Q., Liu, A., & Kusiak, A.

Original source

Tao, F., Qi, Q., Liu, A., & Kusiak, A

Student paper

Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157-169.

Original source

Data-driven smart manufacturing Journal of Manufacturing Systems, 48, 157-169