A large amount of data will be transmitted from (billion or trillion) heterogeneous things to the IoT. Exploring the large volumes of data and extracting useful information from a complex sensing environment at different spatial and temporal resolutions in a fast and effective way is a challenging research problem. The key characteristics of resource constraints in sensor networks (and RFID systems) and high capacity for applications in cloud computing create novel challenges for proposals of adaptive and distributed solutions.In general, heterogeneous sensing devices taking part in the IoT demands the use of multiple sensing modalities and are not connected to an unlimited power supply.
Therefore, efficient energy sensing is a conditioning factor in the design and operation of IoT environments. Therefore, many IoT solutions based on WSN or RFID have to be oriented to low-energy consumption. While such technologies do not still provide enough resources, this is a broad research challenge. Approaches proposed for WSNs  and other low-power technologies can be adapted to deal with the requirements of the IoT.
The internet of things paradigm encompasses several technologies aiming at connecting anything, to be accessed at any time from anywhere. This chapter reviews the state of the art in IoT paradigm, describing standards and architecture models, analyzing different interaction protocols and implementations, to finally come up with a general description of technologies and applications.