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Internet of Things for Indoor Air Quality Monitoring

ISBN-13: 9783030822156 / Angielski / Miękka / 2021 / 82 str.

Jagriti Saini; Maitreyee Dutta; Gonçalo Marques
Internet of Things for Indoor Air Quality Monitoring Jagriti Saini Maitreyee Dutta Gon 9783030822156 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Internet of Things for Indoor Air Quality Monitoring

ISBN-13: 9783030822156 / Angielski / Miękka / 2021 / 82 str.

Jagriti Saini; Maitreyee Dutta; Gonçalo Marques
cena 221,37
(netto: 210,83 VAT:  5%)

Najniższa cena z 30 dni: 212,02
Termin realizacji zamówienia:
ok. 22 dni roboczych.

Darmowa dostawa!
Kategorie:
Technologie
Kategorie BISAC:
Technology & Engineering > Electrical
Science > Environmental Science (see also Chemistry - Environmental)
Computers > Data Science - General
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9783030822156
Rok wydania:
2021
Wydanie:
2021
Ilość stron:
82
Waga:
0.15 kg
Wymiary:
23.39 x 15.6 x 0.51
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

​Jagriti Saini was born in Himachal Pradesh, district Mandi in 1992. She holds a Diploma in Electronics and Communication Engineering (2010) from GPW Kandaghat and completed her B. Tech in Electronics and Communication Engineering (2013) from HPU. She received a Master's Degree in Electronics and Communication Engineering from the National Institute of Technical Teacher’s Training and Research (NITTTR), Chandigarh (Panjab University), India (2017). She was awarded a Gold Medal for securing the highest percentile in the entire university during her Master's Degree. Jagriti is currently pursuing her Ph.D. in Electronics and Communication Engineering from the National Institute of Technical Teacher’s Training and Research (NITTTR), Chandigarh (Panjab University). She is also receiving an INSPIRE fellowship from the Department of Science and Technology (DST), India for carrying out her research work. Her current research interests include Artificial Intelligence, Internet of Things, Environmental Monitoring, Indoor Air Quality Monitoring and Prediction, Healthcare Systems, e-Health, and Autonomous Systems. Her Ph.D. thesis entitled “Design and Development of Intelligent Indoor Air Quality Monitoring and Prediction System - Vayuveda” is mainly focused on developing cost-effective real-time monitoring and prediction system for indoor air quality management. She published more than 25 papers in reputed peer reviewed international journals and conferences. Other than this, she is a frequent reviewer of journals and international conferences and is also working over several edited book projects.


Maitreyee Dutta was born in Guwahati, India. She received the B.E. degree in electronics and communication engineering from Assam Science and Technology University, and the M.E. degree in electronics and communication engineering and the Ph.D. degree with specialization in image processing from Panjab University. She is currently a Professor with the Computer Science and Engineering Department, National Institute of Technical Teachers’ Training and Research, Chandigarh, India. She has more than 22 years of teaching experience. Her research interests include Internet of Things, security of data, IP networks, Internet, authorisation, data privacy, Public Key encryption, pattern clustering, cloud computing, graph theory, program testing, regression analysis, sign language recognition, medical imaging, source code (software), IEC standards, ISO standards, adders, content-based retrieval, and data compression. She has more than 100 research publications in reputed journals and conferences. She completed one sponsored research project—Establishment of Cyber Security Lab—funded by the Ministry of IT, Government of India, New Delhi, amounting Rs. 45.65 lac. Two sponsored Project on Advanced Cyber Security Laboratory of amount 62 lacs funded by MeitY, New Delhi and Securing Billion of Things-SEBOT funded by All India Council of Technical Education, New Delhi of amount Rs. 14.98 lacs are in progress.

Gonçalo Marques holds a PhD in Computer Science Engineering and is member of the Portuguese Engineering Association (Ordem dos Engenheiros). He is currently working as Assistant Professor lecturing courses on programming, multimedia and database systems. Furthermore, he worked as a Software Engineer in the Innovation and Development unit of Groupe PSA automotive industry from 2016 to 2017 and in the IBM group from 2018 to 2019. His current research interests include Internet of Things, Enhanced Living Environments, machine learning, e-health, telemedicine, medical and healthcare systems, indoor air quality monitoring and assessment, and wireless sensor networks. He has more than 80 publications in international journals and conferences, is a frequent reviewer of journals and international conferences and is also involved in several edited book projects. 

This book provides a synthesis for using IoT for indoor air quality assessment. It will help upcoming researchers to understand the gaps in the literature while identifying the new challenges and opportunities to develop healthy living spaces. On the other hand, this book provides insights about integrating IoT with artificial intelligence to design smart buildings with enhanced air quality. Consequently, this book aims to present future scope for carrying out potential research activities in this domain.

Over the past few years, the Internet of Things (IoT) is proven as the most revolutionizing invention in the field of engineering and design. This technology has wide scope in automation and real-time monitoring. Indoor air quality assessment is one of the most important applications of IoT which helps in the development of smart and healthy living spaces. Numerous methods have been developed for air quality assessment to ensure enhanced public health and well-being. The combination of sensors, microcontrollers, and communication technologies can be used to handle the massive amount of field data to access the condition of building air quality.



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