Relation between Contextual Computing and IoT
As IoT (Internet of Things) paradigm grows in a fashion of internet-connected devices, things, and objects, the deployment of sensors, sensors enabled devices, objects, RFIDs, and actuators proliferated significantly over the last few years. Similar to mobile and pervasive computing, IoT deployed solutions is going to leverage the contextual computing capabilities combining contextual applications and context-aware communications. Middleware solutions is expected to address different capabilities like device management, interoperability, platform portability, context awareness, security, privacy, and many more. To combat with this massive data challenges, enterprises need to understand the context data paradigm in terms of collection, modelling, reasoning, adaptation, and distribution.
Contextual computing, often called Context Awareness Computing is the approach of systematic use of software and hardware to collect contexts related data & information of devices, users & environment and analyze it to present relevant information to users based on real time physical condition or pre-set social or location conditions. Contextual computing aims to sense the physical environment of users, time contexts, computing and device surroundings to deliver personalized information to each users based on their location, proximity to objects, social context, activity factors, and environmental condition. In IoT; connected mobile, wearable, or objects performs context-triggered actions for the end users.
From conceptual perspective, context can be divided into primary and secondary context. Primary context identify location, identity, time and activity perspective with the answer of where, who, when, and what. Secondary context answers the question of why derived through a computation process based on primary context data. But in reality, sometime same data can be used as primary context for one application and secondary context for other application. IoT need more specific categorization of context considering the operational perspective such as Physical context, User context, Computing context and Time context to design context aware application or solution.
My research titled “IoT Contextual Computing 2017 – 2022” examines the technologies, companies, and solutions for contextual computing. The report evaluates the combination of IoT with context-aware computing and the integration of AI and Big Data technologies. The report provides forecasts for IoT in Contextual Computing globally and by region by type, sub-type, product, and industry vertical for the period 2017 to 2022. The report benefits include:
- Context-aware computing forecasts 2017 - 2022
- Identify context aware application design strategies
- Understand context lifecycle management strategies
- Learn about personalization, passive active context awareness
- Identity the relationship between IoT and context-aware computing
- Learn about specific challenges and opportunities for contextual computing
- Understand role of sensor fusion and machine learning in contextual computing
- Identify opportunities for monetizing data gathered using Big Data Analytics tools