The Challenges and Emerging Technologies for Low-Power Artificial Intelligence IoT Systems

The Internet of Things (IoT) is an interface with the physical world that usually operates in random-sparse-event (RSE) scenarios. This article discusses main challenges of IoT chips: power consumption, power supply, artificial intelligence (AI), small-signal acquisition, and evaluation criteria. To overcome these challenges, many works recently aimed at IoT system design have emerged. This work reviews the architecture and circuit innovations that have contributed to IoT developments. This paper does not cover security of IoT. Event-driven architectures and nonuniform sampling ADCs significantly reduce the long-term average power. Besides, embedding AI engines in IoT nodes (AIoT) is one critical trend. The computing-in-memory technique improves the energy efficiency of the AI engine. Asynchronous spike neural networks (ASNNs) AI engines show low power potential. In addition to data processing, small-signal acquisition is also critical. The charge-domain analog-front-end (AFE) techniques such as floating inverter-based amplifiers improve energy efficiency. In addition to the above low power and high energy efficiency technologies, energy harvesting can also enhance the lifetime of AIoT devices. This article discusses recent ambient RF and natural energy harvesting approaches and high-efficiency DC-DC with a wide load range. Finally, novel evaluation criteria are introduced to establish benchmark standards for AIoT chips.

I. Introduction

The Internet of Things (IoT) was first described as a large-scale RFID network [1]. Currently, the concept of IoT is broad, and the number of IoT devices is expanding [2]. As shown in Fig. 1, the consumer electronics market has expanded by more than ~20 times every ten years, based on Bell’s law [3], since the 1960s. IoT device development will continue to follow the above law, witnessing continuous reduction in device size, reduction in power consumption, and expansion in market volume. Additionally, there is a trend of combining emerging technologies. For example, the artificial intelligence (AI) IoT, i.e., AIoT, is widely considered. Unlike traditional consumer electronics, the above improvements in AIoT features may not come entirely from CMOS technology scaling. The expected exponential improvements in AIoT technology (Fig. 1) will require more innovations in circuits, systems, design methodologies, and other fields. Fig. 1.

IoT device development will continue to follow the below trends, witnessing continuous reduction in device size, reduction in power consumption, and expansion in market volume [4].