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Enterprise System Integration with Internet of Things
Table of Contents
Enterprise System Integration with Internet of Things    1
Case Study:    3
Introduction    3
Enterprise systems and Internet of things    4
Conclusion    10
References    10
Case Study:
Caterpillar Inc. is a leading manufacturer in the world in the field of mining equipment, industrial gas turbines, diesel-electric locomotives, diesel & natural gas engines etc. The need that Caterpillar had was to have a flexible and intelligent edge solution that will allow modifications by the dealers, partners and customers. It needed user-configurable displays and multi-protocol support in a robust and adaptable platform. It collaborated with Bright Wolf, which is a consultant for implementation of Internet of Things at industries and are known for delivering customizable solutions. The purpose of the association was to build an Internet of Things platform that will form the foundation for the next generation intelligent Caterpillar Marine Displays. It also needed human machine interfaces across various industrial applications such as petroleum pumping, generators, hydraulics, mining and rail road applications. The reason Caterpillar chose Bright Wolf is because it believed in the experience and ability of Bright Wolf to handle complex industrial situation that will be beneficial towards the intention of Caterpillar. Caterpillar had sales revenue of $47 Billion and it is considered among the leading manufacturers. The intention of Caterpillar was to take the organisation to the next level by incorporating Internet of Things into the business process to make the processes more streamlined.
Introduction
Enterprise systems integration with the internet of things is the advance form of technology which enables the reduction of manual work thereby increasing the efficiency in the business. The technology helps to integrate the physical things such as devices used for computing to participate in the processes meant for business. Internet of things is the future as the technology is developing and has reached towards a matured stage as far as the wireless communications is concerned(Mehta et.al. 2018). The technology of inter-communicating devices is also getting matured and has reached a stage that it can be out to commercial use. The paper sheds further light on the concerned matter and shows how the internet of things as well as the enterprise systems is enabled by the latest development like in the sectors of manufacturing, automobile, retail, healthcare and also telecom technologies.
Enterprise systems and Internet of things
The integration of the internet of things with the enterprise systems is used primarily to deliver useful insights in the decision making process to be implemented strategically as the part of the enterprise application projects(Manogaran et.al. 2018). The platform is generally used to acquire data which is relevant for the systems already present in the enterprises as well as to provide maximum controls for managing devices which are used for connecting organisations for data acquisitions. In more general terms organisations mostly adopt the applications based on the internet of things to make the systems cost efficient. The use of the devices that will be helpful in making strategic decisions such as data centres and other devices which are of strategic importance will become more frequent and common in enterprises as they offer technological scalability and make the decision making shorter(Mendoza et.al. 2019). The use of these applications may reduce the consumption of energy or reduction in the failure rate of the products and services. The strategic advantage that the integration can provide is becoming very essential for the organisations which are operating on a global scale. The integration will help these organisations to become more agile and more responsive to any situation because of the use of the technology.
Manufacturing as well as construction companies use the internet of things to reduce the chances of injuries and accidents on the sites, for design of the products and several operations relating to the enterprises(Wang et.al. 2018). The design as well as operation domain of the enterprise for manufacturing involves several types of decision making processes at various levels. The decision making processes require a large amount of time to collect real-time data from different types of organisational processes(Manavalan et.al. 2019). This can be easily done if the enterprise places a system which uses internet of things as the main source of information gathering mechanism. The data is gathered and are transferred to the data centre for later analysis. The enterprise can also use the same system for other processes such as data acquisition, analysis of the data and communication among other processes. Among the many uses for the collected data in these kinds of enterprises by the internet of things is to return the user back certain features personalised to likeness as well as the usage of contextual cues(Wang, 2018). The internet of things helps to establish the means to directly reach the customers using personalised ads in order to generate more revenue compared to other systems. The personalised advertisements can be deployed using the help of artificial intelligence and data mining to understand the behaviour of the customer. Upon understanding the buyer behaviour and the preferences the advertisements can become more potent to introduce the need for the product in the mind of the customer. This increases the chance of getting the product sold and also increases the demand and market reach of the product(Mourtzis et.al. 2018). This implies that the internet of things infrastructure greatly increases the performance of the manufacturing enterprises. It also helps the organisation gain competitive advantage over the other organisation which is not using this technology. The integration will be helpful for manufacturing companies to reduce the greater attrition rate which are normally observed in manufacturing sector.
The rapidly changing situations regarding the automobile manufacturers provide both opportunities as well as challenges(Maldonado et.al. 2018). The opportunities which are present in the disruptive period is the utilisation of the information technology such as artificial intelligence, communications technology and machine learning among others create an added value for the enterprises and tries to translate science fiction into reality. The automobile enterprises with their integration to the internet of things solve many issues such as connectivity, distribution, eco conservation and flexibility in development of vehicles suitable to environment. Some of the key features include integration of independent provider of the services with access to the global and local customer base(Tu, 2018). Vehicles with enabled eSIM for the flexibility and independence of the vehicles with artificial intelligence installed within their systems to make efficient decisions(Preuveneers et.al. 2018). The installation of GPS tracking chips with direct link to the satellites provides accurate details of the terrain and maps. With autonomous vehichles are on the testing phase and some companies have even tried commercial run the use of internet of things will become more greater in automobile industry. The integration with enterprise systems will make the vehicle and the road traffic safer as the technology progresses. The technology implementation as of now in the automobile sector has not been matured and there are flaws in the implementation(Madhikermi et.al. 2019). But as the technological developments happen and better computing equipments capable of handling large amount of data and information is getting used the technology is certain to become more reliable to use(Shi et.al. 2018). Google and Uber have already made some developments in this field, but the problem still remains in the response time of the system as the real world conditions are dynamic and the computer has to handle large amount of data to process very quickly to provide decision to the car driving system for the response to the road conditions(Tabet et.al. 2019). This data acquisition and response mechanism in the field of autonomous driving cars has not...