LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications

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18/05/20 Computer Science Reference this

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LoRaWAN Fog Computing Based Architecture for

IoT Enabled Smart Campus Applications


Abstract: — It is estimated that one trillion IoT devices will be deployed by the year 2025. Many of these will be located on college campuses.  A Smart Campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university. However, these IoT environments generate an unprecedented amount of data which could overwhelm the storage systems and analytics applications in use today.  This paper contends that a LoRaWAN Fog Computing Based Architecture will provide low-power processing and long-range connectivity. This will allow the leveraging of IoT to create the Smart Campus with applications in learning, campus living, and security and safety.

Keywords: Smart Campus, Internet of Things (IoT),  Fog computing, LoRaWAN

1. Introduction

By making ”things” such as consumer electronic devices, home appliances, medical devices, and sensors all part of the Internet environment, the paradigm known as the Internet of Things (IoT) will encourage new interactions between things and humans. IoT envisions a new world of interconnected devices and humans in which quality of life is enhanced and resources are efficiently utilized. McKinsey Global Institute estimates that one trillion IoT devices will be deployed by the year 2025 with a potential economic impact of 11 trillion dollars per year. This would be equivalent to about 11 percent of the world economy, only to be steadily rising within the years to come.1

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The Internet of Things is the concept of connecting any device with an on/off switch to the Internet (and/or to each other). When these sensors and technology are used to connect components across a city to derive data and improve the lives of citizens and visitors, it is called a Smart City. This Smart City concept has been expanded to include the Smart Campus. The vision of the next-generation Smart Campus is an educational institution that uses Internet of Things technology woven seamlessly within a well-architected infrastructure that enables a digitally connected institution that can enhance the campus experience, drives operational efficiency, and provides education in a manner that all can access.2

2. LoRaWAN Fog Computing Based Architecture


One of the major objectives of IoT is real-time analytics and decision making. Although technologies are growing rapidly, most of the current IoT data processing solutions transfer the data to cloud for processing. It is neither scalable nor suitable for real-time decision making to transfer all the data generated by the millions of things to the cloud. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability.3 The use of a LoRaWAN Fog Computing Based Architecture is one of the most recent and most promising developments for managing these requirements.

The dynamic nature of IoT environments, real-time requirements, and the increasing processing capacity of edge devices has led to the evolution of a paradigm called fog computing. The formal definition of Fog computing is “a scenario where a huge number of heterogeneous (wireless and sometimes autonomous) ubiquitous and decentralized devices communicate and potentially cooperate among them and with the network to perform storage and processing tasks without the intervention of third-parties. Users leasing part of their devices to host these services get incentives for doing so.”4 Fog computing extends cloud services to the edge of networks. This results in a reduction in latency through geographical distribution of IoT application components. As data travels from sensors for example towards the cloud, it passes through many devices, which are potential targets for computation offloading. Fog computing uses these intermediate devices for their computational and storage capabilities. The main challenge is in scheduling applications in the devices — from the network edge to the cloud — to meet latency requirements while minimizing resource and energy wastage. In fog computing, the actual minimization of energy wasting is proportioned with decentralization, meaning the data is not distributed and handled within the same system. The end-user and distributor profit from this method, as the initial data run-time is shorter in comparison to both edge and cloud computing. In other words, combining the methodologies of both groups is deemed necessary for the consistencies in following up with the advancements in  modern technology and the IoT.

To go along with low-cost, low-power processing, IoT-driven Smart Campuses’ need low-cost, low-power consumption connectivity to nodes spread throughout a wide area. One solution to this problem is Low-Power Wide Area Networks (LPWANs) which stand in between short-range and long-range cellular-based technologies. These networks exploit sub-GHz, unlicensed frequency bands and are characterized by star topologies and long-range radio links. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is being implemented at the University of A Coruña (UDC), Spain. Its development is carried out by the LoRa Alliance, led by IBM, Actility, Semtech, and Microchip. In the United States, an example of smart campus can be found in West Texas A&M University. The proposed system has already supported diverse IoT projects, such as a LoRaWAN pilot for monitoring environmental conditions or an OpenCV-based smart parking system.3


Figure 1. LoRaWAN Network Architecture

The LoRa network is typically laid out in a star-of tars topology, where the end devices are connected via a single-hop LoRalink to one or many gateways that, in turn, are connected to a common network server over IP protocol as seen in Figure 1. This technology employs a spreading technique in which a symbol is encoded in a longer sequence of bits, thus reducing the signal to the noise and interference ratio required at the receiver for correct reception without changing the frequency bandwidth of the wireless signal. The length of the spreading code can be varied, thus making it possible to provide variable data rates, enabling the possibility of trading throughput for coverage range, link robustness, or energy consumption.5

 When the LoRaWAN Network is combined with fog computing, the resulting communications architecture can be seen in Figure 2. It consists of  three different layers, beginning with the different IoT LoRaWAN nodes deployed throughout the campus. These communicate with LORAWAN gateways that comprise the fog layer. Every fog gateway is essentially a Single Board Computer (SBC) that embeds Ethernet, Wi-Fi, and Bluetooth interfaces along with a LoRaWAN transceiver. Finally, the top layer is the cloud, where user applications meet data storage services.6

Figure 2. LoRaWAN fog-based smart campus architecture.


 There are three different transmission profiles in which LoRa end devices operate. The key difference between these profiles  is  the  trade-off between  latency  and  power consumption. Class A is the default mode and is mainly intended for monitoring applications. Here, transmissions are always initiated by the end devices, in an asynchronous manner. After each uplink transmission, the end device will open two reception windows, waiting for any command or data packet returned by the server. Class B is for battery powered actuators where uplink and downlink transmissions are needed equally. Finally, Class C is for end devices with no energy constraint, which can keep their receive window open at all times.

 LoRaWAN utilizes two layers of security using AES ecryption: one for the network and one for the application. The network security ensures authenticity of the node in the network while the application layer of security ensures the network operator does not have access to the end user’s application data.6

3. Smart Campus Applications

Universities are leveraging IoT to create the Smart Campus with applications in learning, campus living, and security and safety (Figure 3).7 Applications of the Internet of Things in the college classroom begin with flexible learning spaces. Mobile technologies and applications free educators to rethink how they deliver learning. Videoconferencing and digital collaboration tools are used to bring in experts from across campus or around the world and can open classes and lectures to students anywhere, freeing students, faculty and administrators from worrying about space constraints, location or weather. In the same way that Smart Campus technologies free students and faculty from the constraints of physical space, they also afford more flexibility and freedom in time. By recording and archiving all lectures, every second of every lecture can be streamed on demand.

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IoT also has applications in college life such as smart ID cards/smart payments. Smart ID cards can reduce all kinds of campus credentials, thus increasing convenience and security for teachers and students. Another application is building automation. This automation for a campus will save money and still be able to deliver high quality services. Delivery of these services do not limit the aspect of academics but also enhance social, financial, and environmental aspects of a smart campus.  The use of smart lighting can use the same amount of energy but will adjust to reduce costs on the electric bill and reduce light flickering. Devices can save parking information and have sensors to sense if this is the spot purchased or if this the right car. IoT has changed the way we get information in daily life, such as positioning, navigation, and social network check in.

Finally, there are applications that protect the safety and security of students on campus such as video surveillance. On a smart campus, anywhere you have a power source, you can deploy a smart IP video camera and use wireless meshing to connect it. This method is much cheaper and easier than traditional security cameras. These use behavior-based alarms to alert campus security if someone tries to enter a building during off hours or even if a door has been left open. This paired with other assets of security will make it so everyone that comes in and out of the buildings can be monitored. A combination of ubiquitous wireless coverage with location-based services can track anything moving across campus.8 These beacons can be placed anywhere from electronics to people and can track the location of anything. They will send an alert out when something gets out of range of campus.

Figure 3. Technologies and applications in a smart campus.

4. Conclusion

By embracing the vision of a Smart Campus, forward-looking colleges and universities are building a foundation for the future. By creating a single technology infrastructure based on LoRaWANs and fog computing to connect devices, applications and people, they are putting in place a platform to deliver campus services more efficiently and intelligently. They are collecting information from more places, in more ways, to uncover  new insights and improve decision-making. And they are creating a more dynamic and engaging campus that affords better experiences to everyone using it.

5. References

[1] N. Verstaevel, G. Garzone, T. Monteil, N. Guermouche, J. Barthelemy, P. Perez. “An Ontology Based Context-Aware Architecture for Smart Campus Applications.” 2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications. 2018. Accessed 10.27.2019. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8672271&isnumber=8672218

[2] M. Alex, T. Halgali. “Smart Campuses: The Next-Generation Campus.” Deloitte Consulting LLP. Accessed 9.10.2019. https://www2.deloitte.com/us/en/pages/consulting/solutions/next-generation-smart-campus.html

[3] S. Sobhi, A. M. Ali, M. Abdelkader. “Combining Fog Computing and LoRaWAN Technologies for Smart Cities Applications.” The 2nd Europe – Middle East – North African Regional Conference of the International Telecommunications Society: “Leveraging Technologies For Growth”. 02.2019. Accessed 10.27.2019.


[4] Y. Wang. “The Relationships among Cloud Computing, Fog Computing, and Dew Computing.” dewcomputing.org. Accessed 10.27.2019.


[5]  S. Anusiya1, R. Prajula, J. Nithya, J. Nivetha. “LoRa –A Novel Protocol for Long Range Communication.” International Journal of Engineering Research & Technology. 2017. Accessed 10.27.2019.


[6] P. Fraga-Lamas, M. Celaya-Echarri, P. Lopez-Iturri,  L. Castedo, L. Azpilicueta, E. Aguirre, M. Suárez-Albela, F. Falcone, T. Fernández-Caramés. “Design and Experimental Validation of a LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications.” Sensors. 07.2019. Accessed 10.27.2019. https://www.mdpi.com/1424-8220/19/15/3287

[7] “Introducing the Smart Campus.” Ruckus Wireless. Accessed 9.22.2109.


[8] A. Alghamdi, S. Shetty. “Survey Toward a Smart Campus Using the Internet of Things.” 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud). 2016. Accessed 10.27.2019.


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