The number of nodes typically used in sensory networks is growing rapidly, leading to large amounts of redundant data being exchanged between sensory terminals and computing units. To efficiently process such large amounts of data, and decrease power consumption, it is necessary to develop approaches to computing that operate close to or inside sensory networks, and that can reduce the redundant data movement between sensing and processing units. Here we examine the concept of near-sensor and in-sensor computing in which computation tasks are moved partly to the sensory terminals. We classify functions into low-level and high-level processing, and discuss the implementation of near-sensor and in-sensor computing for different physical sensing systems. We also analyse the existing challenges in the field and provide possible solutions for the hardware implementation of integrated sensing and processing units using advanced manufacturing technologies.

通常在传感网络中使用的节点数量正在迅速增长，从而导致在传感终端和计算单元之间交换大量冗余数据。为了有效地处理如此大量的数据并降低功耗，有必要开发一种在传感网络附近或内部运行的计算方法，该方法可以减少传感和处理单元之间的冗余数据移动。在这里，我们研究了近传感器和传感器内计算的概念，其中计算任务部分移至了感官终端。我们将功能分为低级处理和高级处理，并讨论了针对不同物理传感系统的近传感器和传感器内计算的实现。