Current and emerging trends in (I)IoT wireless solutions


Sisinni Emiliano Sisinni

Emiliano Sisinni

University of Brescia, Italy

Ivanovitch Ivanovitch Silva

Ivanovitch Silva

Federal University of Rio Grande Do Norte, Brazil

Ferrari Paolo Ferrari

Paolo Ferrari

University of Brescia, Italy

Dennis Dennis Brandão

Dennis Brandão

University of São Paulo, Brazil

DiegoSilva Diego Silva

Diego Silva

Federal University of Rio Grande do Norte, Brazil


The importance of distributed measurement systems is increasing. The use of the IoT paradigm can be successfully applied to metrology as demonstrated by recent advances of Industry 4.0. In particular, industrial communications are facing the leap forward made by new generation wired and wireless technologies, such as Single pair Ethernet WiFi6, 5G, LPWANs and more. The diversified performance and tradeoffs they offer, mainly derived from the rapid change in consumer market needs, are moving an increasing number of (innovative) industrial applications into the wireless domain. For instance, think about mobile robots and UAVs, nowadays widely used in factories, that require modern distributed systems to include wireless links to connect the IIoT backends via intelligent edge devices, in terms of seamless, standardized and transparent device integration.

However, the appealing possibilities these technologies provide, also pose many challenges, that must be addressed by the research. Scenarios where sensors and instruments are deployed on a wide area, or on mobile systems, remain extremely challenging due to the unreliability and unpredictability intrinsic in wireless links. Security is another main concern.

In particular, research activity is required for optimizing the overall network performance in agreement with the actual application requirements, e.g., in terms of timeliness, determinism, energy consumption, and data extraction rate. For instance, innovative Machine Learning (ML) techniques, possibly applied to software defined / cognitive radios, can be exploited for dynamically adapting communication parameters.

This special session aims to bring together academic and industry professionals to a session where the most recent studies, implementations, and proposals about the issues mentioned above can be presented and discussed.


Submissions are welcomed on (but not limited to):

  • LPWAN systems for measurements;
  • Short range wireless networks for measurement applications (e.g., wireless sensor networks leveraging Wi-Fi, Bluetooth LE and/or IEEE802.15.4);
  • Single Pair Ethernet sensors and their measurement applications
  • 5G/4G mobile communications for measurements applications;
  • In Vehicle and V2X wireless measurement systems;
  • Wireless applications for continuous tracking of product data after-sale (digital twin);
  • Distributed and mobile IoT measurement devices and systems;
  • Safety and security issues in distributed and mobile IoT measurement devices and systems;
  • Wired and Wireless measurement systems for smart environments (e.g., smart industries, buildings and cities);
  • Large scale deployment of wireless sensors (e.g. environment monitoring, localization, fire detection);
  • Applications of wireless measurement solutions to large process plants in Industry;
  • Cloud architecture to manage scalable measurement systems and measurement data platform in large deployment scenario;
  • Recent advances in research domains with similar communication requirements.


Emiliano Sisinni obtained the M.Sc. degree in electronic engineering in 2000 at the University of Brescia. In 2004, he got the Ph.D. in “Electronic Instrumentation” at the same University. He is currently a Full Professor with the Department of Information Engineering at the University of Brescia. He was guest professor at Mid Sweden University for the AYs 2016/2017-2020/2021. His main research topic is the development and the performance evaluation of digital networks for industrial communications, with particular attention to wireless solutions. He has also been involved in the development of digital signal processing of sensory data based on microcontrollers, DSPs and FPGAs. Since 2008 he seats in the committee SC65C - WG16 and WG17 and the TC65C - WG 17 of the IEC (International Electrotechnical Commission).

Ivanovitch Silva received the licentiate, M.Sc., and Ph.D. degrees in Electrical and Computer Engineering from the Federal University of Rio Grande do Norte (UFRN), Natal, Brazil, in 2006, 2008, and 2013. He concluded in 2016 a short course about Big Data & Social Analytics at Massachusetts Institute of Technology (MIT). Since 2013 is professor at Digital Metropolis Institute (IMD,UFRN). He teaches and supervises Ph.D and master students in the Graduate Program of Electrical and Computer Engineering at UFRN. At present, he acts as the coordinator in the Lato Sensu Specialization in Big Data & Analytics at UFRN. His research interests include modeling and scientific data analysis, Internet of Things, Industry 4.0 and Smart Cities.

Paolo Ferrari received the M.Sc. (Hons.) degree in electronic engineering and the Ph.D. degree in “Electronic Instrumentation” from the University of Brescia, Brescia, Italy, in 1999 and 2003, respectively. He is currently a Full Professor with the Department of Information Engineering, University of Brescia. He has authored more than 200 international papers. His current research interests include embedded measurement instrumentation, smart sensors, sensor networking, smart grids, IoT and Industrial IoT, real-time Ethernet, and fieldbus applications. Dr. Ferrari is a member of IEC SC65C MT9, IEC TC65C WG10. In 2013, he received the Technical Award from the IEEE Instrumentation and Measurement Society.

Dennis Brandão graduate at Engenharia Mecânica from Universidade de São Paulo (1998), master's at Mechanical Engineering from Universidade de São Paulo (2000) and ph.d. at Mechanical Engineering from Universidade de São Paulo (2005). Currently, he is associate professor at the Departamento de Engenharia Elétrica, Escola de Engenharia de São Carlos, Universidade de São Paulo . He has experience in Mechanical Engineering, acting on the following subjects: automação industrial, fieldbus foundation, wireless sensors, profibus and Real Time Ethernet fieldbus.

Diego Silva is an Associate Professor at the Federal University of Rio Grande do Norte. He has experience in Computer Engineering, with emphasis on Industrial Automation, where he has been developing projects for the Brazilian industry since 2003 in various topics such as alarm management, connectivity and industrial protocols, asset management and data visualization. In addition, he has also been involved in technological development projects in the areas of education and building automation. His interests include Industry 4.0, IoT, IIot, signal processing, big data, cloud computing, among others. He did postdoctoral studies at the University of Southern California between 2015 and 2016, where he delved into the subject of Digital Signal Processing in Graphs and he was an official Visiting Professor to the University of Brescia in 2018.