This experimentation scenario is similar to F2F1, in the sense that it does not involve any nodes that are mobile. However, different than Scenario 1, in this mode, we will consider communication between a fixed tower and a fixed node on the ground / inside a building. Similar to the previous case, this platform will be available to experimenters on a continuous basis conditioned on resource constraints, and will not require AERPAW personnel on the field. In this scenario, the “PAW” depicted in the figure above may not necessarily be equipped with any companion computer and may simply be an inexpensive IoT (e.g., LoRa) sensor.

A good example of this experimentation scenario is the Thoreau testbed at the University of Chicago, where, Sigfox and LoRa gateways continuously collect data from sensors that are deployed under the soil. NSF SAGE mid-scale infrastructure is another example that collects data from IoT sensors, with applications in a wide range of settings, ranging from wildfire detection to snowflake classification and water-level detection.

We highlight, as a few examples, IoT, AR/VR, with references to several related works in the literature. There are also various experimentation possibilities with next-generation smart agriculture, cities, buildings, and health. Experimenters can measure the link qualities between an IoT access point (AP) and sensors deployed in different environments (soil, buildings, roads, etc), for different weather conditions and seasons, different environments/distances, and over different time periods for the farming and agriculture industries. Similarly, the experimenters can use the IoT APs for the smart-health care applications.

IoT experiments (e.g. LoRa, NB-IoT)

[1] A. Puschmann, P. Sutton, and I. Gomez, “Implementing NB-IoT in Software – Experiences Using the srs LTE Library,” arXiv e-prints, p. arXiv:1705.03529, May 2017.
[2] W. Ayoub, A. E. Samhat, F. Nouvel, M. Mroue, and J. Prevotet, “Internet of mobile things: Overview of LoRaWAN, DASH7, and NB-IoT in LPWANs standards and supported mobility,” IEEE Commun. Surveys Tuts., vol. 21, no. 2, pp. 1561–1581, 2019.

AR/ VR experiments

[1] K. Apicharttrisorn, B. Balasubramanian, J. Chen, R. Sivaraj, Y. Z. Tsai, R. Jana, S. Krishnamurthy, T. Tran, and Y. Zhou, “Characterization of multiuser augmented reality over cellular networks,” in Proc. IEEE Int. Conf. Sensing, Commun., and Netw. (SECON), 2020, pp. 1–9.
[2] S. K. Datta, “Virtual reality mobile application testing in a 5G testbed,” in Int. Conf. Ubiquitous Future Netw. (ICUFN), 2019, pp. 455–459.

Smart Agriculture

[1] D. Vasisht, Z. Kapetanovic, J. Won, X. Jin, R. Chandra, S. Sinha, A. Kapoor, M. Sudarshan, and S. Stratman, “Farmbeats: An IoT platform for data-driven agriculture,” in Proc. USENIX Symp. Networked Systems Design and Implementation (NSDI), 2017, pp. 515–529.
[2] M. Gupta, M. Abdelsalam, S. Khorsandroo, and S. Mittal, “Security and privacy in smart farming: Challenges and opportunities,” IEEE Access, vol. 8, pp. 34 564–34 584, 2020.
[3] B. D. Grieve, T. Duckett, M. Collison, L. Boyd, J. West, H. Yin, F. Arvin, and S. Pearson, “The challenges posed by global broadacre crops in delivering smart agri-robotic solutions: A fundamental rethink is required,” Global Food Security, vol. 23, pp. 116–124, 2019.

Smart Cities

[1] H. Menouar, I. Guvenc, K. Akkaya, A. S. Uluagac, A. Kadri, and A. Tuncer, “UAV-enabled intelligent transportation systems for the smart city: Applications and Challenges,” IEEE Commun. Mag., vol. 55, no. 3, pp. 22–28, 2017.
[2] Z. A. Baig, P. Szewczyk, C. Valli, P. Rabadia, P. Hannay, M. Chernyshev, M. Johnstone, P. Kerai, A. Ibrahim, K. Sansurooah, et al., “Future challenges for smart cities: Cyber-security and digital forensics,” Digital Investigation, vol. 22, pp. 3–13, 2017.
[3] E. Vattapparamban, I. Guvenc, A. I. Yurekli, K. Akkaya, and S. Uluagac, “Drones for smart cities: Issues in cybersecurity, privacy, and public safety,” in Proc. IEEE Int. Conf. Wireless Commun. Mobile Computing (IWCMC), Paphos, Cyprus, Sep. 2016.
[4] J. Kakar, A. Chaaban, V. Marojevic, and A. Sezgin, “UAV-aided multi-way communications,” in Proc. IEEE Annual Int. Symp. on Personal, Indoor and Mobile Radio Communications (PIMRC), 2018, pp. 1169–1173.

Smart Buildings

[1] D. Minoli, K. Sohraby, and B. Occhiogrosso, “IoT considerations, requirements, and architectures for smart buildings—energy optimization and next-generation building management systems,” IEEE Internet of Things J., vol. 4, no. 1, pp. 269-283, 2017.
[2] H. Ghayvat, S. Mukhopadhyay, X. Gui, and N. Suryadevara, “WSN-and IOT-based smart homes and their extension to smart buildings,” Sensors, vol. 15, no. 5, pp. 10 350–10 379, 2015.

Smart Health

[1] K. Shankar, M. Ilayaraja, and K. S. Kumar, “Technological solutions for health care protection and services through the internet of things (IoT),” Int. J. Pure and Applied Mathematics, vol. 118, no. 7, pp. 277–283, 2018.
[2] M. S. Shahamabadi, B. B. M. Ali, P. Varahram, and A. J. Jara, “A network mobility solution based on 6LoWPAN hospital wireless sensor network (NEMOHWSN),” in 2013 Seventh Int. Conf. on Innovative Mobile and Internet Services in Ubiquitous Computing. IEEE, 2013, pp. 433-438.
[3] S. M. R. Islam, D. Kwak, M. H. Kabir, M. Hossain, and K. Kwak, “The internet of things for health care: A comprehensive survey,” IEEE Access, vol. 3, pp. 678– 708, 2015.