Wearable and IoT devices requiring positioning and localisation services grow in number
exponentially every year. This rapid growth also produces millions of data entries that need …

This paper presents PlanIoT, a middleware approach for enabling adaptive data flow
management in IoT-enhanced spaces (eg, buildings) using automated planning …

In applications such as elderly care, dementia anti-wandering and pandemic control, it is
important to ensure that people are within a predefined area for their safety and well-being …

Indoor location-based services rely on the availability of sufficiently accurate positioning in
indoor spaces. A popular approach to positioning relies on so-called radio maps that contain …

This paper presents SmartSPEC, an approach to generate customizable smart space
datasets using sensorized spaces in which people and events are embedded. Smart space …

Emerging domains, such as sensor-driven smart spaces and social media analytics, require
incoming data to be enriched prior to its use. Enrichment often consists of machine learning …

Smart space administration and application development is challenging in part due to the
semantic gap that exists between the high-level requirements of users and the low-level …

Localization in GPS-denied outdoor locations, such as street canyons in an urban or
metropolitan environment, has many applications. Machine Learning (ML) is widely used to …

We describe ENRICHDB, a new DBMS technology designed for emerging domains (eg,
sensor-driven smart spaces and social media analytics) that require incoming data to be …

This paper develops a query-time missing value imputation framework, entitled ZIP, that
modifies relational operators to be imputation aware in order to minimize the joint cost of …