A.A. 2020/21

The SMART ENVIRONMENTS (DATA SCIENCE) A.A. 20/21 lessons and material are available on the e-learning MOODLE platform


Once the student is registered on this web page he/she can browse the webpage on


Evey lessons will be partially in presence and partially online (50% blended modality on the basis of the matricula number). Students shall reserve seats in the ROOM via PRODIGIT.

 On-line lesson will be available with ZOOM at the following link, starting from March 31st for the Prof. CUOMO part, during the lesson hours:


 The lessons from 23rd of February will be given by Prof. Mauro Biagi (visit his bacheca for the zoom link).

 On-line meetings are available with GOOGLE MEET (see the instructions on Teacher Bacheca).


  • Basics of digital communications and networking (TCP/IP based)
  • Wireless systems

Outline of the Course

  • Enhanced Services by Smart Devices 
  • Data Acquisition, Coding, and Aggregation in Smart Environments 
  • Device Communication and Networking
  • Practical examples of Data Processing for Smart Environments

Course Object

Goal of this course is to provide an overview of the large world of wireless and wired technologies that are will be used for the Smart Environments. These technologies will be able to provide infrastructures of networks and digital information used in the urban spaces and smart environments to build advanced applications. Recent advances in areas like pervasive computing, machine learning, wireless and sensor networking enable various smart environment applications in everyday life. The main goal of this course is to present and discuss recent advances in the area of the Internet of Things, in particular on technologies, architectures, algorithms and protocols for smart environments with emphasis on real smart environment applications. The course will present the communication and networking aspects as well as the processing of data to be used for the application design. The course will propose two cases studies in the field of smart environments: Vehicular Traffic monitoring for ITS.

Final exam

The final exam can be done in two ways:

Option 1 (valid if one has the oral exam within end of July 2021):

Homework* (10/30)

• Oral with Prof. Biagi (10/30)

Oral with Prof. Cuomo (10/30)

* The homework is a tutorial paper to write singularly or in a group of a maximum number of 2 students.

Option 2 (Always valid):

Written exam (one question to be answered by writing) (10/30)

Oral with Prof. Biagi (10/30)

Oral with Prof. Cuomo (10/30)

Aule ed orari (rooms and timetable)
50% in presence
 Martedì 15:00-18:00
Aula A4 (Via Ariosto - RM102)

 Mercoledì 10:00-13:00
Aula XII (Palazzina Tumminelli Città Universitaria - CU007)

Google Group 2020_21

Teaching material

 Lectures Useful links


 LoraWAN Tutorials


  1. Cook, Diane J., and Sajal K. Das. "How smart are our environments? An updated look at the state of the art." Pervasive and mobile computing 3.2 (2007): 53-73.
  2. M. R. Palattella et al., "Internet of Things in the 5G Era: Enablers, Architecture, and Business Models," in IEEE Journal on Selected Areas in Communications, vol. 34, no. 3, pp. 510-527, March 2016. doi: 10.1109/JSAC.2016.2525418
  3. Smart Environments: Technology, Protocols and Applications (Wiley Series on Parallel and Distributed Computing) Wiley-Interscience ©2004 "http://onlinelibrary.wiley.com.ezproxy.uniroma1.it/book/10.1002/047168659X"
  4. Gupta, Akhil, and Rakesh Kumar Jha. "A survey of 5G network: Architecture and emerging technologies." IEEE access 3 (2015): 1206-1232.
  5. Lora alliance. [Online]. Available: https://www.lora-alliance.org/
  6.   Leduc, Guillaume. "Road traffic data: Collection methods and applications." Working Papers on Energy, Transport and Climate Change 1.55 (2008).J. Zhang, F.-Y. Wang, K. Wang, W.-H. Lin, X. Xu, and C. Chen, Data-driven intelligent transportation systems: A survey," IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 1624{1639, 2011.

Francesca Cuomo,
28 gen 2019, 06:16