Focused Sessions

The rapid growth of connected devices has transformed the way sensors are deployed across healthcare, industry, agriculture, environment, and smart cities. However, the increasing volume of raw data generated by these sensors presents challenges in terms of bandwidth, energy consumption, latency, and privacy. This Focus Session will explore the emerging paradigm of edge intelligence embedding machine learning and advanced analytics directly into sensing devices to enable real-time, secure, and energy-efficient decision-making.
The session will bring together researchers, practitioners, and industry experts working at the intersection of sensing, TinyML, federated learning, and multimodal sensor fusion. Topics of interest include novel algorithms and hardware architectures for resource-constrained sensors, energy harvesting for intelligent devices, federated and privacy-preserving learning across distributed sensors, and deployment case studies in real-world domains such as biomedical monitoring, predictive maintenance, and climate resilience.
By bridging theory and practice, this session aims to showcase cutting-edge solutions and identify key challenges that must be addressed to realize the vision of autonomous, intelligent, and trustworthy sensing systems. Participants will gain insights into how edge intelligence can redefine the future of sensing by enabling faster responses, reduced data dependence, and greater scalability.

The Artificial Intelligence of Things (AIoT) combines artificial intelligence (AI) technology with the Internet of Things (IoT) infrastructure in order to develop more effective IoT operations, increase interactions between humans and machines, optimize data management and analytics. An essential aspect of AIoT is the application of AI to a specific thing. In its most basic form, this entails conducting AI on the device, also known as edge computing, with no external connections required. AIoT does not require an Internet; it is just a development of the IoT concept, and the resemblance ends there. The combined potential of AI and IoT promises to unleash untapped consumer value across a wide range of business verticals, including edge analytics, autonomous cars, customized fitness,
remote medical care, precision cultivation, intelligent retail, automated upkeep, and manufacturing machinery automation.

The proposed session focuses on using human sensing and data analytics to detect, interpret and respond to human behavior to improve marketing effectiveness and to gain insights into customers’ motivations, preferences, and decisions. This will help in creative advertising, product development, pricing, and other marketing areas.  Traditional marketing revolves around the key principles of Product, Price, Place, Promotion, People (or Positioning), Process and Physical Evidence (or Packaging). Surveys, interviews of consumers or focus group studies are used to evaluate the effectiveness of the marketing strategies. Studies have shown that neuroscience techniques are better than traditional methods such as survey and interviews which are subjective in nature, often biased and unable to capture the unconscious decision-making process. Also, subjective assessments are conducted pre/post facto and not during the experience. Neuroscientific studies have proven that most decision-making is primarily an emotional, impulsive or unconscious action and seldom based on rational processing of information. Thus, application of neuroscientific knowledge can help brands to make smarter decisions based on how people’s brain truly reacts rather than what they say. Various sensing methodologies like EEG, fMRI, Eye-tracking, camera and physiological signals like GSR, Heart rate variability are now a days being used to understand customer behaviors, optimizing product design and packaging, developing personalized marketing strategies and enhancing customer experiences. Therefore, we expect some research works that will apply some of the human sensing technologies to solve challenges faced in the field of marketing and advertising.