Design and Simulation of IoT Systems Using the Cisco Packet Tracer

Design and implementation of Internet of Things (IoT) systems require platforms with smart things and components. Two dominant architectural approaches for developing IoT systems are mashup-based and model-based approaches. Mashup approaches use existing services and are mainly suitable for less critical, personalized applications. Web development tools are widely used in mashup approaches. Model-based techniques describe a system on a higher level of abstraction, resulting in very expressive modelling of systems. The article uses Cisco packet tracer 7.2 version, which consists of four subca-tegories of smart things—home, smart city, industrial and power grid, to design an IoT based control system for a fertilizer manufacturing plant. The packet tracer also consists of boards—microcontrollers (MCU-PT), and sin-gle boarded computers (SBC-PT), as well as actuators and sensors. The model facilitates flexible communication opportunities among things—machines, databases, and Human Machine Interfaces (HMIs). Implementation of the IoT system brings finer process control as the operating conditions are monitored online and are broadcasted to all stakeholders in real- time for quicker action on deviations. The model developed focuses on three process plants; steam raising, nitric acid, and ammonium nitrate plants. Key process parameters are saturated steam temperature, fuel flowrates, CO and SO x emis-sions, converter head temperature, NO x emissions, neutralisation temperature, solution temperature, and evaporator steam pressure. The parameters need to be monitored in order to ensure quality, safety, and efficiency. Through the Cisco packet tracer platform, a use case, physical layout, network layout, IoT layout, configuration, and simulation interface were developed.


Introduction
Internet of things (IoT) and Internet of Services (IoS) concepts are a major part of the broad industry 4.0 technologies. These interconnected things and services enable modern smart factories and integrated value chains to function optimally.
Today's connected and data driven world is disruptive and gives businesses a competitive advantage. Ubiquitous cloud services enable the deployment of IoT applications anywhere and offer complete control. IoT technologies will ensure systems established in Industry 4.0 are of low cost and have lean operating systems. Industry players must be prepared for unprecedented changes that IoT brings [1] [2] [3] [4]. IoT technologies such as RFID, wired and wireless sensor networks, and embedded systems enable the digitization and virtualization of shared resources and capabilities in the services and manufacturing industries for access through the cloud. Mell and Grance [5] define Cloud Computing (CC) as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. The cloud is mainly categorized as private cloud, community cloud, public cloud and hybrid cloud [6]. Today's business space is characterized by smart environments/spaces and self-aware things such as smart transport, products, cities, buildings, rural areas, energy, health systems, wholesale and retail outlets.
The spread of real-time data across companies-given the availability of appropriate analytical tools and methods-can have a significant impact on the entire company. Organizations that use IoT, digitization, and big data technologies have been evaluated as having a higher level of logistic service, more efficient processes with their partners, improved cooperation between certain logistic functions, and higher market and financial performance and competitiveness [7]. Countries that promote the use of high technology achieve more efficient production processes, which lead to better productivity and economies of scale.
The German Ministry of Education and Research established Industry 4.0 as a roadmap to promote the German high-tech industry and its strategy [8] [9]. The ubiquitous computing era presents enterprises with huge quantities of data, known as Big Data. The data is gathered through smart sensors among physically networked objects.
Although there is much hype about IoT and related technologies, practical rollout still remains depressed. There are many underlying reasons for the mismatch between what exists on the ground and the promises being made. Adoption of new unknown technologies is a risky activity and is currently expensive [10]. Lack of creation and consistent implementation of a corporate digital N. Gwangwava [13]. The engineering of IoT systems is another challenge for industry practitioners responsible for design and deployment. Challenging aspects which they face include safe programming and validation, achievement of resilience and graceful degrading, as well as the development of new tools and methods [14]. IoT infrastructure and ecosystem should promote reusability, interoperability integration, modular programming, better flexibility, agility and, ease of maintenance. Internet connectivity is crucial for the success of IoT technologies in industry. "Any Thing" and "Every Thing" should be interconnected with the global information and communication infrastructure. This can be achieved through network accessibility (getting on a network) and compatibility (common ability to consume and produce data) [15]. Although the internet protocol version 6 (IPv6) was introduced to solve the problem of the shortage of IP addresses experienced with IPv4, its global implementation has challenges.
Each connected device and "being" requires a unique IP address, which makes the network complex and difficult to manage, all the connected sensors need to be powered, and parallel management of different protocols and legacy assets during the transition period is a complex task [16]. It also looks at visual programming for IoT systems and the extended perspective of IoT, which is the Internet of Everything (IoE). Section 3 covers the methodology used to design and simulate the IoT platform for the fertilizer manufacturing company, the results and discussion. Section 4 concludes the article.

Literature Review
This section reviews literature on standard definitions for IoT, associated technologies, layered architecture, extended view of IoT, i.e. IoE, and lastly visual programming languages (VPLs).

Internet of Things (IoT) Definition and Technologies
The definition of IoT continues to evolve. IoT represents electrical or electronic devices, of varying sizes and capabilities, which are connected to the Internet.
The scope of the connections has grown beyond just machine-to-machine communication (M2M) to broadly focused machine-to-people (M2P), and people-to-people (P2P) communications [18] [19]. M2M is mainly being utilized to implement "smart factories" using IP networks to inter-connect physical infrastructure with sensors, which results in extra capabilities such as analytics and monitoring using technologies such as radio frequency identification (RFID).
M2P is used to capture and analyze consumer data to be used in designing products and services such as mobile marketing to push the manufacture-consumer relationship as close to the consumer as possible. P2P utilizes converged network services such as real-time video collaboration tools with "Bring Your Own Device" (BYOD) capabilities [20]. IoT can also be defined as a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer in- Things in "IoT" can refer to anything which possesses smart characteristics, such as sensors, embedded chip, automobile, people, animal, agricultural produce or anything in the value chain, road infrastructure, building or anything in the built environment, consumer goods, plant equipment or machinery, and many others. When these "Things" are provided with unique identifiers (UIDs), they gain the ability to transfer data over a network with no need for human-to-human or human-to-computer interaction. "Things" equipped with UIDs can sense each other and communicate, can be accessed and interacted with over the Internet. Specific functionality that is aided by these features is remote access for monitoring, configuration, and troubleshooting, and data analysis. This changes how, where, and who makes decisions in the modern data-driven world. IoT helps private and public enterprises to find more operating efficiencies, deliver greater value to customers, employees, and citizens in general, and enable new business models. Each IoT device provides capabilities-features or functions-it can use on its own or in conjunction with other IoT and non-IoT devices to achieve one or more goals [12]. These capabilities are provided in Table 1. Provide the ability for computing devices to interact directly with physical entities of interest. Every IoT device has at least one transducer capability. The two types of transducer capabilities are given below: Sensing: The ability to provide an observation of an aspect of the physical world in the form of measurement data. E.g. temperature measurement, radiographic imaging, optical sensing, and audio sensing. Actuating: The ability to change something in the physical world. E.g. heating coils, cardiac electric shock delivery, electronic door locks, servo motors, and robotic arms.
Interface capabilities: Enable device interactions (e.g., device-to-device communications, human-to-device communications). Examples are: Application interface: The ability for other computing devices to communicate with an IoT device through an IoT device application. E.g. an application programming interface (API).
Human user interface: The ability for an IoT device and people to communicate directly with each other. E.g. touch screens, haptic devices, microphones, cameras, and speakers.

Internet of Things (IoT) Architecture
IoT architecture serves to illustrate how various technologies relate to each other and to communicate the scalability, modularity and configuration of IoT deployments in different scenarios [15].  Figure 1 shows the detailed five (5) layer IoT architecture. The architecture is pyramid shaped to resemble the plant automation pyramid.

Internet of Everything (IoE)
The term "Internet of Everything" was used by Cisco since the year 2012, but later on dropped at the dominance of IoT as the preferred term [38]. The Internet of Everything (IoE) brings together people, process, data, and things to make   Many modern consumer electronic devices, which are also present in organizations' facilities, are now connected IoT devices-kitchen appliances (refrigerators, microwave ovens, cooking stoves, etc), thermostats, home security cameras, door locks, light bulbs, and TVs. CIoT is used to refer to applications and uses cases to track personal "assets"-(asset tracking), such as pets, and skateboards, connected "smart home appliances" such as connected refrigerators, washing machines, light bulbs, etc [23]. Industrial Internet of Things (IIoT) describes typical industry use cases across a range of sectors such as manufacturing industries or utilities, smart cities and smart metering [41]. Web of Things (WoT) has been used to describe approaches to facilitate services offered at Open Systems Interconnection model (OSI)'s application layer [42].

Visual Programming and Deployment of IoT
In order to realize the full potential of IoT, there is a need to integrate ubiquitous smart devices and cloud based applications [43]. A combined IoT framework with a cloud at the center, gives the flexibility of dividing associated costs in the most logical manner and is also highly scalable. In the combined framework, sensing service providers can join the network and offer their data using a

Methodology
The article seeks to explore short development life cycle for IoT projects using a set of cloud based platforms and VPLs. A practical use case for a fertilizer man- Tracer can be run on standard programs or can be customized by programming them with Java, Phyton or Blockly.

Company Process Flow
The company's overall process flow diagram is shown in Figure 3. Key process plants that need to be interlinked together are the steam raising plant (boiler house for producing dry steam at 13 bars using coal fired boilers), nitric acid plant (produces 57% nitric acid for use in the production of ammonium nitrate), and ammonium nitrate plant (exothermic neutralization of nitric acid and ammonia). The smart factory use case is illustrated in Figure 4. Major process parameters that need to be monitored for the three plants are saturated steam temperature, converter head temperature, and neutralisation temperature respectively.

IoT System Development
When creating IoT simulations, it is advisable to utilize different physical layers in order to be able to adjust the environment variable to influence the IoT devices' behaviour. Figure 5 shows the physical separation of the smart fertilizer manufacturing factory, where three containers are used to physically split the network.
The network for the IoT system is logically separated into three areas: factory (shopfloor sensors), ISP servers (main control centre) and streets (end user devices), as shown in Figure 6. All IoT devices for the smart factory are connected to the router in the control centre. Factory floor sensors are wired to the microcontroller, which is in turn wirelessly connected to the home gateway. The control    This mode helped to physically visualize and troubleshoot any kind of network, for example setting up pings, or more complex packages between nodes. Figure   7 shows the simulation panel, whilst Figure 8 shows the real time flow of data packets.