posted by organizer: aguerrieri || 649 views || tracked by 3 users: [display]

IoT-ES4CB 2021 : Springer Book on IoT Edge Solutions for Cognitive Buildings

FacebookTwitterLinkedInGoogle

 
When N/A
Where N/A
Submission Deadline Sep 30, 2021
Notification Due Oct 15, 2021
Final Version Due Nov 15, 2021
Categories    springer book   IOT   cognitive buildings   edge intelligence
 

Call For Papers

----------------------------------------------------
Springer Book on

IoT Edge Solutions for Cognitive Buildings

Series on Internet Of Things - Technologies, Communications, and Computing
(http://www.springer.com/series/11636)

Call for Contributions
----------------------------------------------------


For any question, request, or proposal contact us by answering this email or by writing an email to the book editors listed at the end of this email.


INTRODUCTION:
-----------------------
The evolution of the Internet of Things (IoT) has introduced a new paradigm for smart buildings that supports a decentralized architecture where a great deal of analytical processing can be done at the edge instead of the cloud or central servers. This computing approach often called "edge computing" or "fog computing" provides real-time intelligence and greater agility of control while, at the same time, offloading heavy communications traffic. By providing edge devices with greater intelligence, the IoT can be more responsive to user preferences and needs.

According to this vision, a building is no longer a static body of matter but a dynamic flow of data that drives the new concept of building as a service provider for users. With so much useful data to be captured and utilized, facility managers can use future developments to their advantage, giving them more insight into energy usage, space optimization, and other efficiencies that can positively impact their operations.

The evolution of automated and intelligent buildings goes towards cognitive buildings, which means a learning building that adapts to user needs, preferences, and changing conditions. Machine learning is a tool that allows making reliable and repeatable decisions by learning from historical relationships and trends in data.

Cognitive buildings go beyond a set of intelligent systems that, collectively, make a building more efficient and functional. They seek to bring these systems together under a new level of intelligence, which coordinates these systems to achieve high levels of optimization and enable buildings to adapt to their occupants’ needs and requirements.

Cognitive buildings can make their occupants more comfortable, more productive, and more healthy; they are buildings that think, learn, and act with intelligence and context awareness. They can sense their environments and also identify problems before they occur. This combines the use of detailed facility management capabilities and cognitive computing to drive towards better-managed buildings. Making buildings smarter can save energy, optimize spaces, and improve safety and security, while also allowing for customizations that suit each occupant's needs.

This book aims to offer a broad overview of the Cognitive Internet of Things applied to cognitive buildings and will give insight into platforms, solutions, and applications in this field.

In particular, the book will gather contributions about topics such as:

● Self-learning and adaptive environments
● Artificial Intelligence and Machine learning for cognitive buildings
● Architectures, Platforms, methodologies, and tools for cognitive buildings
● Innovative Cognitive Applications
● Cloud, Fog, and Edge computing for IoT-enabled buildings
● Big-data and IoT Analytics at the edge
● Building performances and analysis
● Thermal, visual, and air comfort management systems
● Risk assessment and management
● Predictive maintenance of building plants and systems
● Demand-side energy management
● Building sustainability
● Healthiness and healthcare in cognitive buildings
● Human-in-the-loop systems and environments
● Digital twin and simulation for cognitive buildings
● Analysis of building dwellers’ needs and requirements


MANUSCRIPT GUIDELINES:
-----------------------
Details on the format of the paper to submit can be found at
https://www.springer.com/gp/authors-editors/book-authors-editors/your-publication-journey/manuscript-preparation

The paper can be submitted through the Easychair system to the link https://easychair.org/conferences/?conf=iotes4cb
Each chapter is expected to be at least 20 pages and no more than 25 pages.


IMPORTANT DATES:
-----------------------
- Chapter Proposal /Abstract submission: July 31st, 2021
- Submission Deadline: September 30th, 2021
- Review Deadline: October 15th, 2021
- Camera Ready Paper: November 15th, 2021


EDITORS AND CONTACTS:
-----------------------
Franco Cicirelli, ICAR-CNR, franco.cicirelli@icar.cnr.it
Antonio Guerrieri, ICAR-CNR, antonio.guerrieri@icar.cnr.it
Giandomenico Spezzano, ICAR-CNR, giandomenico.spezzano@icar.cnr.it
Andrea Vinci, ICAR-CNR, andrea.vinci@icar.cnr.it

Related Resources

IEEE COINS 2022   IEEE COINS 2022: Hybrid (3 days on-site | 2 days virtual)
Federated Learning in IOT Cybersecurity 2021   PeerJ Computer Science - Federated Learning for Cybersecurity in Internet of Things
IJSCAI 2021   International Journal on Soft Computing, Artificial Intelligence and Applications
DKMP 2022   10th International Conference on Data Mining & Knowledge Management Process
DMML 2022   3rd International Conference on Data Mining & Machine Learning
IEEE COINS 2022   Internet of Things IoT | Artificial Intelligence | Machine Learning | Big Data | Blockchain | Edge & Cloud Computing | Security | Embedded Systems |
blockchain_ml_iot 2021   Network and Electronics (MDPI) Joint Special Issue - Blockchain and Machine Learning for IoT: Security and Privacy Challenges
IoTBDS 2022   7th International Conference on Internet of Things, Big Data and Security
DLIS 2022   Deep Learning for IoT Security - Frontiers in Big Data Journal
IEEE COINS 2022   International Conference on Omni-Layer Intelligent Systems Internet of Things IoT | Artificial Intelligence | Machine Learning | Big Data | Blockchain | Edge & Cloud Computing | Se