Adaptive Learning Analytics

Adaptive learning analytics is a range of analytics algorithms that is performed by sensors and mobile devices to make intelligent analyses of real-time data. The algorithms tune the data stream processing parameters according to the occurring situations and available computational resources such as battery charge and available memory to make the most optimum decision or recommendations.

For example, in a smart room scenario, rather than monitoring sensed context from light, noise and motion sensors individually, this information can be used to reason about situations, such as “meeting”, “presentation” or “study”, providing a better understanding of the environment. It also provides a more abstract view of the environment, rather than focusing on individual pieces of context. Such information output is also formulated, based on optimisation of the computational resources of the sensing devices, and reduces the volume of data needed to be sent to backend systems for analytics processing.

IPv6 and 6LowPAN 
IPv6 is 128-bit Internet address scheme that is used to replace IPv4 addresses which were officially exhausted in February 2011 (in the Asia Pacific Network Information Centre or APNIC). With IPv6, there are approximately 3.4×1038 unique IPv6 addresses, more than enough address space to accommodate the universe of cloud-ready devices for the foreseeable future. IPv6 allows network auto-configuration, making devices easy to be managed and configured automatically once they are in the network. IPv6 can bring about efficient allocation and management of addresses by distributing addressing space in a hierarchical manner. For example, IPv6 addresses allocated to an organisation can be further distributed according to the topology of network infrastructure. Alternatively, IPv6 addresses can be assigned according to geographical regions within a country i.e. North, South, East and West and further allocated based on street levels and building levels. By having an efficient allocation scheme for IPv6 addresses, it allows better manageability, usability and ease of devices identification.

6LoWPAN is an acronym for “IPv6 over Low power Wireless Personal Area Networks”. It is a communication standard that allows the low-power devices to communicate and exchange data via IPv6. There are many benefits of using IP-based connectivity to form the sensor access network:

•  IP connects easily to other IP networks without the need for translation gateways or proxies. 
•  IP networks allow the use of existing network infrastructure. 
•  IP is proven to work and scale. Socket API is well-known and widely used 
•  IP is open and free, with standards, process and documents available to anyone. It encourages innovation and is well understood. 

6LowPAN works on the IPv6 protocol suite based on IEEE 802.15.4 standard. Hence it has the characteristics of low-cost, low-rate and low-power deployment. The bottom layer adopts the physical (PHY) and media access control (MAC) layer standards of IEEE802.15.4, and uses IPv6 as the networking technology.

IOT applications that require a two-way, low-power communication network would benefit from the use of 6LoWPAN. For example, in smart grid systems, a power plant can transmit electric power and messages to clients. On the other hand, clients can also send information to the power plant. Through two-way communications, the power utilisation can be adjusted in a more efficient way. With its affordability and practicality, 6LowPAN presents significant opportunities for the market. 

More than five years 

Nanotechnology 

Nanotechnology is enabling the development of devices ranging from one to a few hundred nanometers. At this scale, a nanomachine is defined as the most basic functional unit and is integrated with nano-components to perform simple tasks such as sensing or actuation. Coordination and information sharing among several nanomachines will expand the potential applications of individual devices both in terms of complexity and range of operation. 

The U.S. National Nanotechnology Initiative has described four generations of nanotechnology development26 with the first generation being nanostructures, materials designed to perform one task. The second phase sees the introduction of active nanostructures for multitasking, for example, actuators and sensors. The third generation, occurring around 2010, featured nanosystems with thousands of interacting components. From now till 2015, integrated nanosystems, functioning with hierarchical systems within systems to perform complexity tasks, will emerge

With nanotechnology, future sensors designs can get much smaller, less power hungry, and more sensitive than current sensors. Sensing applications will thus enjoy benefits far beyond those offered by existing technologies such as MEMS. In the areas of power generation and storage, nanotechnology uses nanomaterials that can dramatically reduce the size of energy storage devices and increase the energy density of the same devices.