Impact of LoRA and 5G on Smart Manufacturing from Automation Perspective

Muhammad Ayoub Kamal^{1, 2}, Muhammad Mansoor Alam ^{1, 3}, Aznida binti Abu Bakar Sajak^1,* and Mazliham Mohd Su’ud⁴

¹Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia
²Institute of Business and Management. Karachi, Sindh, Pakistan
³Riphah International University, I-14/3 Islamabad, Pakistan
⁴Malaysian France Institute (MFI), Universiti Kuala Lumpur, Malaysia
E-mail: muhammad.ayoub@s.unikl.edu.my; ayoub.kamal@iobm.edu.pk; mansoor@unikl.edu.my; m.mansoor@riphah.edu.pk; aznida@unikl.edu.my; mazliham@unikl.edu.my
*Corresponding Author

Received 22 November 2021; Accepted 07 January 2022; Publication 05 April 2022

Abstract

The Industrial Internet of Things (IIoT), also known as Industry 4.0, is a forward-thinking industrial era in which numerous developing technologies are combined to produce digital solutions. In industrial enterprises, Industry 4.0 technologies are separated into base and front-end technologies. Cloud computing, IoT, analytics, and big data are all essential technologies. In this article, we evaluate the current landscape of factory automation and the influence of 5G and LoRA communication on smart manufacturing automation, while front-end technologies are split into four categories: smart goods, smart working, smart manufacturing, and smart supply chain. First, we looked at the idea of Industry 4.0, as well as the four front-end dimensions and four basic technological components. Second, we spoke about smart industrial automation and the influence of 5G and LoRA communication. The broad use of front-end technology, of which Smart Manufacturing is a crucial component, is required for Industry 4.0 to succeed. However, the implementation of the foundation technologies is difficult. Current automation standards will serve as a solid foundation for future smart manufacturing systems. The distribution, adoption, and development of relevant morality in a requirement-driven process may result in faster, deeper, and bigger implementation of smart industrial automation.

Keywords: LoRA, 5G, industrial IoT, automation, long range, fifth generation, industry 4.0, smart manufacturing.

1 Introduction

Industry 4.0, or the fourth industrial revolution, is one of the most quickly evolving issues in both industry and academia [1, 2]. The key component of this concept is Smart Manufacturing [3]. It also considers the plant’s inclusion using the whole product lifetime and supply chain events [4] and the way employees work [5]. As long as data is valuable to the industrial system, Industry 4.0 relies on digital technologies’ suitability to fold data in real-time and evaluate it [6]. The beginning of cloud services, Internet of Things (IoT), analytics, and big data, complete this imaginable, Creating the Industry 4.0 concept of a cyber-physical system (CPS) [7]. Manufacturing companies’ composite technology planning is equivalent to the Industry 4.0 concept [6], one of the key concerns in this innovative manufacturing period. Hence, the actual execution of Industry 4.0 technologies is still a question of investigation [8]. Industry 4.0 run through many pillars which are (cloud computing [9], mobile technology [10], machine to machine communication[11], 3D printing[12], cognitive computing [13], cyber security [14], bigdata [15], RFID technologies [16], advanced robotics and Internet of things [17]).

Figure 1 Industry 4.0’s technology components [18].

Integrating several pieces of equipment in an automation system is critical for optimizing and improving production processes. In recent years, the growth of equipment and automation systems has placed a greater emphasis on this topic, particularly to improve communication between components of a solution. Current automation architectures demonstrate the need for flexibility and adaptability, and compatibility between manufacturers for optimal and efficient systems. The influence of exponential technologies (additive manufacturing, autonomous robots, the Internet of Things, and other Industry 4.0 technologies) as an accelerator or catalyst in industrial processes is a fundamental characteristic of today’s production systems [19]. The requirement of ubiquitous information exchange for automation systems is not a prerequisite of conventional hierarchical models, which allows new systems focusing on integrated functions to emerge. These features enable all equipment to be connected in real-time and communicate information, independent of its hierarchical tier. The common connection between all computers on the same platform reduces data loss due to secondary communication errors and helps intelligent systems to make more rapid judgments. As a result, unified architectures are being used as a support to satisfy Industry 4.0 standards across a wide range of solutions, regardless of platform or vendor. These topologies allow for direct communication between the controller and the equipment without a computer to handle and display data. New automation architecture is presented to consider the notion of Industry 4.0 and provide intelligent solutions for more efficient processes. We study the present state of factory automation and the impact of 5G and LoRA communication on smart manufacturing automation in this article, with front-end technologies divided into four categories: smart products, smart working, smart manufacturing, and smart supply chain. We started with an overview of Industry 4.0, including the four front-end dimensions and four essential technology components. Second, we discussed smart industrial automation and the impact of 5G and LoRA technology. Rest of the paper is structured with Section 2: background of the study. Section 3: smart manufacturing and its technologies. Section 4: role of automation in manufacturing. Section 5: recent trends in automation. Section 6: impact of LoRA on industry 4.0. Section 7: impact of 5G on industry 4.0. Section 8: discussion and Section 9: conclusion.

2 Background

In 2011, a German central regime venture with schools and private enterprises created Industry 4.0. It was part of a purposeful plan to expand progressive cremation arrangements to boost state business productivity and competence [3]. This concept denotes a creative industrial step in engineering designs by engaging in a group of evolving and converging technologies that increase the value of a product across its entire lifetime [4]. This innovative industrial step requests socio-technical progress of humanoid part in manufacture arrangements, in which completely occupied events of the worth restraint will be completed with smart methods [20, 21] besides stranded in information and communication technologies (ICTs) [22]. The notion of innovative manufacturing, often known as Smart Manufacturing, lies at the heart of Industry 4.0. A flexible framework in which stretchable outlines automatically govern creation operations for various items and changing circumstances [23]. This allows for increased quality, production, flexibility, and the ability to produce changed items in large quantities and cost-effectively with reduced resource consumption [24]. Industry 4.0 also examines data sharing and the creation of a Smart Supply Chain, which coordinates manufacturing with dealers to reduce travel times and information changes that result in bullwhip assets [25]. This incorporation also allows corporations to pool capital in collective manufacturing [26], enable them to concentrate on their core skills while sharing product development capabilities at the start of the industry, a shared determination to grow products, and harmonizing resources and amenities, all while adding value [27, 28]. Smart Products, or machines employed in the final product, are part of the greater Industry 4.0 concept. Smart Products can help with new product development by providing data-driven replies [29] and novel services and outcomes for clients [30]. As a result, some experts consider Smart Products the next main goal of IIoT. At the same time, they also allow for creative product-service systems, for example, to create new options for manufacturers and facility providers [31].

Figure 2 History of IR 4.0 [32].

The author examines the second layer of Ir 4.0, referred to as “base technologies,” which underpin all of the other “Intelligent” scopes discussed. The foundation technologies are gathered through new ICT, including IoT, big data, cloud services, and analytic [33]. These technologies are the measured base because they exist in entire magnitudes and dissimilar systems of such magnitudes. They influence the IIoT magnitudes and build the connectivity between probable besides they deliver the intellect of the innovative manufacturing schemes. IoT signifies incorporating computing and sensors in an internet atmosphere via wireless communication. Current developments on the Internet fruitfully permitted numerous things, accomplishing this idea. This was also reinforced by employing the price-decrease of sensors in the current years [23], which empowered detecting any type of entity and their linking to a wider system. Cloud facilities empower on-request network entrée to a public pool of computing capital [34]. This technology takes the volume to accumulate data in an internet server benefactor, which can remain simply recovered over a remote entree [35]. Hence, Cloud amenities help incorporate dissimilar devices; meanwhile, they don’t require to stay adjacent and smooth; they can share info and manage events. The grouping of through Cloud and IoT allows dissimilar apparatus to be associated, assembling enormous volume of information, which consequences in Big Data storage [36]. The data gathered from systems and objects is known as big data, for example, sensor readings. Organized with analytics. Machine learning and data mining are measured as one of the utmost significant motorists of the IR 4.0 and an important foundation of inexpensive benefit for the upcoming [37]. Its top ranking is based on the amount of data it can create. To make digital clones of the plant, you’ll need big data, and analytics allows for increasing analytical volume, allowing for the early detection of events that might disrupt production. The use of analytics and big data may keep production lines self-associating and improve decision-making events across the board for an industrial corporation [15]. The four technologies named cloud, IoT, analytics, and big data have diverse abilities. IoT goals are to resolve communication problems amongst all substances and systems in a plant, whereas cloud facilities offer an informal entree to info and services. Eventually, analytics and big data are essential facilitators for Industry 4.0 progressive applications. At the same time, the system’s cleverness is susceptible to the massive number collected and volume of assessing using progressive methods. As a result, concentrating on the core component of IR 4.0.

Q.1 What is Smart Manufacturing and Its Technologies

2.1 Smart Manufacturing

Smart Manufacturing technologies effort utilizing the fundamental column of the internal operations activities in the fundamental of the Industry 4.0 idea [37], though Smart Invention consider the outside worth-added of products, at what time client data and info are combined with the creation system. These two magnitudes take into account technologies that directly impact industrial goods. Smart Manufacturing evaluates the types of machinery used in a manufacturing system, whereas Smart Products considers the types of machinery used in a product offering. Let’s pretend that Smart Manufacturing is the foundation and key driver of IR 4.0; Smart Product, on the other hand, is an extension of it. This concept tracks the present continuous expansion of the IR 4.0 concept, which has its origins in progressive industrial structures and their connections to other corporate developments [38].

Figure 3 Smart manufacturing [39].

2.2 Smart Manufacturing Technologies

We divided the various types of machinery into six essential reasons for the Smart Manufacturing measurement: (i) linkages, (ii) emulation, (iii) automation, (iv) transparency, (v) agility, and (vi) power management. Plant’s vertical integration includes progressive ICT structures that assimilate all classified stages of the corporation from plant level to mid and upper administration stages serving decision-making activities to be less reliant on humanoid involvement. The first step toward comprehensive vertical integration at the plant level is digitizing physical goods and limitations using Programmable Logic Controllers (PLC), sensors, and actuators [40]. Supervisory Control and Data Acquisition are then used to collect the data used for plant-level production control and analysis. Manufacturing Execution Systems (MES) get information from SCADA on the decision-making information layers and provide that production position to the enterprise resource planning system. Once entire structures are properly connected, production command Information travels downstream from ERP to MES and then to SCADA, assisting in the organization of enterprise capitals interested in manufacturing instructions [40]. Consequently, vertical integration offers further control and transparency of production procedure and assists to expand the plant-level decision-making procedure. To improve adaptableness aimed at dissimilar products, Smart Manufacturing contains interacted types of machinery at plant level, over machine-to-machine communication (M2M)[3]. M2M is a communication system with interconnectivity that allows devices to operate independently, facilitating their integration into manufacturing processes. This capability is maintained by computer-generated appointing, which matches the various PLC codes of the apparatuses and authenticates practically setup activities, minimizing protracted interruption due to longer apparatus configuration. Smart Manufacturing also promotes more automation [3]. Machines can achieve tasks employing more accuracy than in the earlier, collective production though being much less likely to tiredness. intended to automatize functioning procedures comprised it by way of a portion of the smart manufacturing measurement, though the last is planned to work through people, supportive responsibilities that assistance to improve person’s output and flexibility [41]. Hence, remained comprised of collective machines utilizing the technology of the smart working measurement. Furthermore, artificial intelligence gives backing aimed at Smart Manufacturing in numerous ways. Progressive, systematic apparatuses can examine data received from devices to screen and estimate equipment letdowns, surpluses, and other concerns. This allows for analytical preservation, which helps to eliminate disruptions due to unanticipated letdowns throughout the manufacturing process. Artificial intelligence-enabled machines may also detect product irregularities in prior stages of the manufacturing process and cumulative quality control, and shrinking production budgets. Furthermore, due to last-minute orders and procedures constraints, artificial intelligence to rivals’ systems like ERP, anticipating long-term manufacturing needs and modifying them into everyday manufacture instructions [41]. Devices are used in raw materials and finished goods at the plant’s storage for internal traceability. This improved record management supports recall actions by providing overproof of the identity of particular devices within groupings of full items. Inside traceability can also support flexible structures using flexible outlines [42]. Machines recognize the product’s needs in the gadgets that have been implanted in them and take the required steps to develop them. Stretchy lines can also include modular technology that is simply incorporated into a manufacturing line with the least effort. This enables the creation of a wide range of items in small batches with the least amount of production damage [43]. Stabilizer manufacturing is a promising Industry 4.0 technique for accumulating and modifying items. Preservative manufacturing entails 3-dimensional printing of digital models that may be changed for personalization while employing the same capitals. Preservative manufacturing also encourages justifiable manufacturing, as it first needs a unique procedure that creates less surplus than conventional manufacturing. Though, for huge-scale manufactures, the usage of preservative manufacturing is still imperfect due to its little throughput speediness [44, 45]. Finally, to improve plant proficiency, Smart Manufacturing likewise encompasses energy managing. Proficiency monitoring is based on data assortment of energy utilization in electrical power networks. Still, it is improved by intelligent energy management systems that schedule focused manufacturing stages at periods of favorable energy rates. Manufacturing corporations can pay attention to diverse desires they may have as soon as they arrange the execution of the Smart Manufacturing machinery. Though current verdicts of the literature have revealed that the business fluctuates in the profits predictable by person types of machinery for manufacturing performance, corporations must think systemically about the execution of such machinery to accomplish a progressive maturity level of IR 4.0. This proposes that manufacturing types of machinery can be consistent and produce collaboration for the IR 4.0 determinations. The incorporation of smart Manufacturing machinery assisted by IoT outputs is known as cyber-physical systems (CPS). One of the key concepts of Industry 4.0 is the inclusion of physical plant items through the virtual dimension of the plant and merged data, artificial intelligence, and recreation.

Q.2 What is the Role of Automation in Manufacturing?

3 Automation in Smart Industrialized

The ambition for automation presents no signs of narrowing, with innovative manufacturing midpoints progressively needing automation types of machinery to be assembled in. ‘Smart’ manufacturing has developed the watchword aimed at corporations in the trade. The Siemens Smart Manufacturing Invention Centre in Chengdu, China, for the occasion, opened on 21 May this year. Ericsson, in the meantime, is preparing to open an automatic smart plant in the United States in 2020 [46]. In a manufacturing background, automation receipts numerous methods. 3D printers eliminate humanoid error from the calculation, quality control software increasing output, or machines able to accumulate parts with unequalled speediness and exactness. In current ages, this action has remained boosted through the growth of machinery types through machine learning and AI.

Empowering the ‘smart’ manufacturing of the upcoming, such progressions assistance to saturate computerized solutions with potentials of human hands. For example, a ‘dumb’ 3D copier will remain to design uniform if there is a disappointment in the procedure, degenerative capitals. A ‘smart’ result commissioning machine learning and AI, though, could recognize letdown and take actions to terminate or resume the procedure [46, 47]. Aimed at automating smart manufacturing systems, apparatuses, devices, systems, and individuals can be linked via M2M communication networks, producing a manufacturing system in which info carriers exchange machine data in nearby real-time [48]. Data-driven disseminated intellect will empower the speedy formation of a system of manufacturing objects to cost-efficiently yield a variety of modified products with self-motivated batch scopes instantaneously [49]. Specifically, smart manufacturing schemes should have the subsequent features: Modularity: Smart manufacturing schemes are modular, intelligent to organize sub-apparatuses to form diverse system formations to yield innovative modified products cost efficiently [50]. Context-awareness: Smart manufacturing schemes can distinguish, understand and investigate the aims of substances, structures, and contributing handlers in the application area, which permits self-awareness concerning information nearby its status, condition, and possibilities for activities to be reserved [51]. Data-driven decision-making: Smart manufacturing makes widespread usage of perceptions educated as of large production data to make intellectual and adaptive verdicts rendering to altering outward and interior circumstances. Self-organization: Contributors (e.g., methods, schemes, and individuals) can interconnect through respective others and organize their activities in a determined substance deprived of outward participation. Self-organization is classically personified as self-optimization, self-formation, and self-healing proficiencies.

Q.3 What are the Most Recent Trends in Automation?

4 Automation Technology’s Most Recent Trends

The constant exchange of data is the foundation of distributed automation systems. To conduct operations self-sufficiently of uninterrupted humanoid interaction, data stream between sensors, controllers, and actuators is required [52]. The introduction of automation technologies remained what is now known as the IR 3.0 after the introduction of steam power to alleviate employees of difficult manual labour and mass manufacturing based on job separation [53]. To enable info conversation, a gathering of industrial communication systems progressed through the ages, initial or after the 1980s. It is remarkable that these expansions, in numerous cases, selected and lodged novel technologies evolving in other areas, mainly in the ICT world. Web technologies, Ethernet, and wireless networks are specimens of this cross conception. These innovative technologies formed novel occasions for the creation info conversation more complete. Therefore, automation systems might raise further composite moreover. The up-to-date tendencies manipulating automation technology stay the emerging tactile Internet, IoT, and CPS. For the concluding [54], discussions industrial automation through an important, progressively increasing application arena. These ideas are not completely novel and occurred in the background of ICT some years before. They are, however, strong industrial automation systems with a variety of viewpoints from which people look at automation systems [55].

Furthermore, they back current trends, such by way of attaining an advanced degree of inter-linking, reasoning automation, and everchanging info gathering and dispensation into cloud-based applications [56]. Spread over the thoughts of IoT and CPSs to the manufacturing automation area directed to the meaning of the Industry 4.0 impression, where 4.0 refers to an IR 4.0 empowered by Internet technologies to produce smart products, smart manufacture, and smart facilities. Established in Germany, the span has rapidly become a slogan on a worldwide ruler [57]. By way of a gentle of the answer with comparable areas, Although the Industrial Internet initiative was founded in the United States, it should be noted that the word was used much earlier. From the perspective of communication, CPSs and IoT trust mainly on telecommunication networks and moveable Internet, which have not amused yourself the main character in industrial communication. Furthermore, They require Internet access, which was never considered in factory automation before. As a result, telecom and IT networks may not meet the precise requirements for dependable, predictable, and well-organized communication through automation. This seems to be changing right now. In terms of real-time automatic engagement, this is a game-changer. On the other hand, the telecom sector has identified industrial automation as a possible application area for its goods. It looks committed to taking automation into account in the growth of fifth-generation (5G) networks. Both advancements, which are made up of integrated and semantic data based on web values, have the potential to transform the way industrial networks are built. They might be a prerequisite for achieving industrial Internet of Things (IIoT) and CPSs.

Q.4 What is the Impact of LoRA on Industry 4.0?

5 LoRA (Long Range) for Industry 4.0

To achieve low power consumption for M2M (machine to machine) applications, current technology developments entail the introduction of new protocols and long-distance communication architectures, considering the limitations imposed by wireless sensor networks such as long distances, high speed, and low power consumption [58]. Wireless technologies important to and connected to the IoT sector offer a variety of coverage ranges ranging from a few inches to tens of kilometres. You may utilize technologies like Bluetooth, Wi-Fi, ZigBee, and 6LowPAN for short and medium distances, and LoRA, Sigfox, or GSM for long distances, depending on the transmission distance [59]. Because of its low cost and low power, LoRaWAN [60] is the most widely used LPWA technology. The document outlines LoRaWAN’s capabilities and limitations [61].

Table 1 Comparison study related flying ad hoc networks

Parameter	Value	Symbol
Code Rate	1	CR
Bandwidth	125 kHz	BW
Frequency	902.3; 902.5;…; 903.7 MHz	fc
Spreading Factor	7; 8; 9; 10; 11; 12	SF
Transmission Power	20 dBm	–
Antennas Gain	3 dBi	–
Noise Figure	7	NF

LoRa is gaining traction in several areas, including smart cities, smart metering, health monitoring, fleet/goods tracking, energy management systems, and other monitoring applications where existing technologies, such as the IEEE 802.15.4 standard, have proven to be successful and efficient. Low-power, low-cost communication technologies such as LoRa [62] and Bluetooth Low Energy [63], which were not initially designed for industrial contexts, have recently been effectively adapted for usage in industrial applications.

Figure 4 Long range (LoRA) usage in industry 4.0 [64].

Q.5 What is the impact of 5G on Industry 4.0?

6 5G’s Impact on Industrial Automation

Digital revolution is the fundamental of IR 4.0, and 5G network setups will be important supportive resources. In the succeeding period, the manufacturing business is predictable to grow in the direction of a disseminated group of manufacture, with associated things, small-energy methods, cooperative machines, and combined logistics and manufacturing. These ideas are particularly personified below the Industry 4.0 pattern and commanded numerous application circumstances demarcated by an occupied collection of the German Podium Industry 4.0 [65]. Individual driving application setup is a network of geologically disseminated plants with the stretchy adaptation of manufacturing competencies and allocation of capital and resources to expand directive contentment. Amongst other things, consistent widespread-area communication is desirable for this situation. By way of a consequence of these alterations, upright industries will have boosted technical dimensions offered to generate the expansion of innovative products and facilities. An upright in this situation denotes a structure of end-user objects being in the right place to a certain industry. They exist on topmost of the interacted assembly via termination-toned transmission facilities due to the 5G network. The network proposes concurrent communication both inside and between upright assemblies. In Europe, the next generation of networks is seen as a reciprocal system encompassing wireless and cable communication systems, with public and private communication providers providing virtualized and actual transmission responsibilities. Because of the method’s heterogeneity, providing a set of relevant application assistances to end handlers will be a must. It’s also important to think about what end handlers need. End handles are also seen as uprights in this circumstance. Such requirements have been discussed and written out in a white paper for the upright plants of the future [66]. An investigation of the conforming necessities demonstrations that latency below 5ms reliability, and density up to 100 devices/m $^{2}$ , along with fitted limitations on the ground or residents’ exposure, are the utmost vital achievement targets 5G desires to accomplish for supportive entirely probable facilities of the five studied areas. Furthermore, with worldwide accessibility of immediate communications, guaranteed QoS, and price stages suitable to encounter clients’ prospects, 5G will overlay the method for innovative commercial chances. Moreover, the necessities from the diverse uprights have been combined into a general idea of 5G [67]. A mutual assembly has remained established, comprising diverse layers with precise stages of thought. 5G networks will evolve intellectual transposition phases. The 5G architecture is planned to support a wide range of use cases, each with its own set of requirements, such as coverage, capacity, flexibility, and latency. Another key issue is offering cloud infrastructure and end-to-end network services in the form of shares over the same physical setup to fulfil upright-precise standards while simultaneously providing mobile broadband services. For example, a logical network assembly via apparatuses may be such a piece, as long as application responsibilities and application relationships are maintained between them. They include requirements for QoS in solitary relationships. A segment will be animatedly plotted on a dynamic network.

Figure 5 5G in industry 4.0 [68].

7 Discussion

Initially, it has been confirmed that IR 4.0 is connected with the usage and application of the Internet and computers as an important part of IR 3.0 [69]. The role of communication technologies likes, LoRA and 5G is very important. The sub-apparatuses of IR are recognized in using technology aimed at socio-economic growth. Regardless of the circumstance, literature recognizes IR 4.0, thought that the industrial stage of development of the previous is dissimilar from the existing information stage of development. However, as contended by, info is still an important part of IR 4.0. Hereafter, IR 4.0 automation and digitization [70] can be merged into the entrepreneurship profession. The conclusions have more established that automation and digitization are pointers of technical apparatuses for pleasing to the eye socio-economic growth [71]. Research has publicized that the exclusion of some works that want humanoid contribution [72]. The literature imagines that some humanoid works would remain removed regardless of the fact. However, work that needs extreme decision-making assistance and management cannot be removed with automation and digitization by way of fundamental elements of IR 4.0. The conclusions of this paper presented that there will be alteration in jobs when organizations contribute to the element of IR 4.0 automation and digitization. There will be additional jobs in the country, and previous jobs will not endure the challenge of IR 4.0.

8 Conclusion

This article looks at smart industrial automation and digitalization, as well as the impact of 5G and LoRA on these processes. Smart manufacturing skills open the way for a future in which highly personalized things may be mass-produced at cheap costs utilizing easily available self-directed production processes. Smart manufacturing, in our opinion, has developed a phrase with unexpected interpretations as a creative concept. However, impressive research progress on the fundamental investigation challenges of smart manufacturing remains insufficient. Significantly, smart industrial automation requires low-latency ICT support, and 5G aids in the automation and digitization of the manufacturing business. 5G networks will lead to the development of intellectual platforms. External technologies are used to stimulate the real automation sector. The important necessities constantly endured unchanged to conversation info about manufacturing procedures in an appropriate, consistent, and perhaps unvarying means. The nonappearance of an optimal technology to encounter these areas encouraged engineers. It encouraged an assembly of various and mismatched solutions, and the demands for combined methods stayed overheard but not observed. We believe that current standards have laid a solid foundation for developing smart manufacturing automation solutions organized with connectivity, progressive algorithms, and computation equipment. However, we believe that much work remains to be done to achieve interacted self-forming manufacturing that responds to energetic fluctuations in the manufacturing environment. In future author will present work with respect to low power and wide range technology that which technology has more potential with respect to industry 4.0.

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Biographies

Muhammad Ayoub Kamal, pursing PhD in (Information Technology), from the Malaysian Institute of Information Technology University Kuala Lumpur, Kuala Lumpur, Malaysia. He received his Master of Engineering degree in Information Technology and Bachelor of Engineering degree in Computer System Engineering from Mehran University of engineering and Technology in 2015, 2012 respectively. He is working as a lecturer in Computer Science Department of IoBM. He has seven years of experience in fieldwork and academic institutions, five years of experience as IT Manager in EKTA construction company, and he has one year of experience as Lecturer Computer Science in ILMA University. He has published 9 research articles in national and international research journals. His areas of research are wireless sensor network (WSN), long range technology (LoRA), internet of things (IoT), machine to machine communication (M2M), machine learning (ML) and artificial intelligence (AI).

Muhammad Mansoor Alam holds a PhD Degree in computer engineering, a PhD Degree in electrical and electronic engineering, the M.E degree in system engineering, and M.sc degree in computer science. He is a Professor of Computer Science in riphah international university. He is also working as an adjunct professor in UniKL. He is an active researcher in the field of Computer Science. He has authored more than 160 research articles published in ISI indexed journals, as book chapters, and in peer-reviewed conferences. He is also an author of the book “Study guide of Network Security” copyrighted by Open University Malaysia and Open University Hong Kong.

Aznida binti Abu Bakar Sajak Graduated from University of Liverpool in 2005 with Masters of Science (Engineering) in Telecommunications and Microelectronics System. Loves Liverpool so much that she decided to pursue her PhD at the same university sponsored by the Islamic Development Bank, Saudi Arabia. Aznida Abu Bakar Sajak was in Digi Telecommunications, a mobile service provider in Malaysia owned by Telenor ASA of Norway for almost six years before joining UniKL in 2011. Holds a PhD in Electrical Engineering and Electronics from the University of Liverpool in 2019. A member of Board of Engineers Malaysia, The Institution of Engineers, Malaysia and The Institution of Engineering and Technology, UK.

Mazliham Mohd Su’ud received a PhD in Computational Intelligence & Decision, from University De La Rochelle, France 2007. He received his Postmaster Degree in Electronics, from University De Montpellier II France and master’s degree in electrical and electronics engineering from the University of Montpellier II, in 1993, and since 2013. He has been a President/Chief Executive Officer of Universiti of Kuala Lumpur, Malaysia. He is an active researcher in the field of machine learning algorithms. He has authored more than 70 research articles published in ISI indexed journals, as book chapters, in peer-reviewed conferences, and Scopus journals.