Citation: Sharma, A.; Sharma, V.;
Jaiswal, M.; Wang, H.-C.; Jayakody,
D.N.K.; Basnayaka, C.M.W.;
Muthanna, A. Recent Trends in
AI-Based Intelligent Sensing.
Electronics 2022, 11, 1661. https://
doi.org/10.3390/electronics11101661
Academic Editor: Junseop Lee
Received: 31 January 2022
Accepted: 6 May 2022
Published: 23 May 2022
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Review
Recent Trends in AI-Based Intelligent Sensing
Abhishek Sharma
1,†
, Vaidehi Sharma
1,†
, Mohita Jaiswal
1,†
, Hwang-Cheng Wang
2,†
,
Dushantha Nalin K. Jayakody
3,
* , Chathuranga M. Wijerathna Basnayaka
3,4,†
and Ammar Muthanna
5
1
Department of Electronic and Communication Engineering, The LNM Institute of Information Technology,
Jaipur 302031, India; abhisheksharma@lnmiit.ac.in (A.S.); vaidehisharma444@gmail.com (V.S.);
mohitajaiswal166@gmail.com (M.J.)
2
Department of Electronic Engineering, National Ilan University, Yilan 260007, Taiwan; hcwang@niu.edu.tw
3
COPELABS, Lusófona University, 1749-024 Lisbon, Portugal; chathurangab@sltc.ac.lk
4
Centre for Telecommunication Research, School of Engineering, Sri Lanka Technological Campus,
Padukka 10500, Sri Lanka
5
Department of Applied Probability and Informatics, Peoples’ Friendship University of Russia (RUDN
University), Miklukho-Maklaya St, 117198 Moscow, Russia; ammarexpress@gmail.com
* Correspondence: djayakody@autonoma.pt
† These authors contributed equally to this work.
Abstract:
In recent years, intelligent sensing has gained significant attention because of its au-
tonomous decision-making ability to solve complex problems. Today, smart sensors complement and
enhance the capabilities of human beings and have been widely embraced in numerous application
areas. Artificial intelligence (AI) has made astounding growth in domains of natural language pro-
cessing, machine learning (ML), and computer vision. The methods based on AI enable a computer
to learn and monitor activities by sensing the source of information in a real-time environment. The
combination of these two technologies provides a promising solution in intelligent sensing. This
survey provides a comprehensive summary of recent research on AI-based algorithms for intelligent
sensing. This work also presents a comparative analysis of algorithms, models, influential param-
eters, available datasets, applications and projects in the area of intelligent sensing. Furthermore,
we present a taxonomy of AI models along with the cutting edge approaches. Finally, we highlight
challenges and open issues, followed by the future research directions pertaining to this exciting and
fast-moving field.
Keywords:
artificial intelligence; machine learning; intelligent sensing; datasets; neural networks;
IoT; learning algorithms
1. Introduction
The term “Smart Sensor” was coined in the 1970s [
1
]. The word “Smart” is related
to the capability of microelectronic devices having operative intelligence features. The
improvements observed in the 1980s, especially those related to the area of sensor tech-
nology, show perfection in signal extraction, real-time data transfer, and adaptability to
the physical environment by sensors, which helps in fetching data that seemed to be inac-
cessible previously. In the 1990s, intelligence was added to devices and more promising
results were observed in this area. The evolution in intelligence technology was due to
the advancement in computational technologies. Such intelligent devices possess three
main features: (i) extraction of signal information, (ii) signal processing, and (iii) instruction
execution. It is interesting to observe that applied intelligence was also being advanced
at the same time. In the 1980s, machine learning, and later, in the 1990s, deep-learning,
were also in a progressive state. Artificial intelligence covers all the important technological
development in this domain, including RNN, CNN, Transfer Learning, Continual AI, etc.
Thus, both smart Sensors and AI are integrated to form intelligent sensing for the develop-
ment of smart applications. It is important to observe that nowadays sensors are not just
Electronics 2022, 11, 1661. https://doi.org/10.3390/electronics11101661 https://www.mdpi.com/journal/electronics
