DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning

DTMM is a library designed for efficient deployment and execution of machine learning models on weak IoT devices such as microcontroller units (MCUs). The motivation for designing DTMM comes from the emerging field of tiny machine learning (TinyML), which explores extending the reach of machine learning to many low-end IoT devices to achieve ubiquitous intelligence. Due to the weak capability of embedded devices, it is necessary to compress models by pruning enough weights before deploying. Although pruning has been studied extensively on many computing platforms, two key issues with pruning methods are exacerbated on MCUs: models need to be deeply compressed without significantly compromising accuracy, and they should perform efficiently after pruning. Current solutions only achieve one of these objectives, but not both. In this paper, we find that pruned models have great potential for efficient deployment and execution on MCUs. Therefore, we propose DTMM with pruning unit selection, pre-execution pruning optimizations, runtime acceleration, and post-execution low-cost storage to fill the gap for efficient deployment and execution of pruned models. It can be integrated into commercial ML frameworks for practical deployment, and a prototype system has been developed. Extensive experiments on various models show promising gains compared to state-of-the-art methods

Driving Simulation Study on Speed-change Lanes of the Multi-lane Freeway Interchange

AbstractBecause of the interactions of the multi-lane freeway mainline, upstream, downstream, the diversity of environmental conditions, as well as the complexity of geometric configuration, speed-change lanes of the multi-lane freeway interchange present greatest safety and operational challenges for drivers. Most freeway crashes occur in the vicinity of interchange diverging and merging areas, especially in speed-change lanes. In this paper, the UC-win/Road5 software was used as the technical tool, and a three-dimensional driving scene was built. Multi-lane freeway field data were used for the calibration of model parameters. The geometry configuration of the speed-change lanes as well as the driving behavior characteristics such as speed, acceleration rate, glancing in the diverging and merging areas were studied in this paper. Based on the driving simulation study in the areas, results supply a valuable technical reference for speed-change lane geometry configuration, the length design of speed-change lane, the operational safety evaluation of multi-lane freeway diverging and merging areas, also the operation and management of multi-lane freeways

A new volumetric strain-based method for determining the crack initiation threshold of rocks under compression

The crack initiation stress threshold ( ci) is an essential parameter in the brittle failure process of rocks. In this paper, a volumetric strain response method (VSRM) is proposed to determine the σci based on two new concepts, i.e., the dilatancy resistance state index ( ci) and the maximum value of the dilatancy resistance state index difference (| ci|), which represent the state of dilatancy resistance of the rock and the shear sliding resistance capacity of the crack-like pores during the compressive period, respectively. The deviatoric stress corresponding to the maximum | ci| is taken as the ci . We then examine the feasibility and validity of the VSRM using the experimental results. The results from the VSRM are also compared with those calculated by other strain-based methods, including the volumetric strain method (VSM), crack volumetric strain method (CVSM), lateral strain method (LSM) and lateral strain response method (LSRM). Compared with the other methods, the VSRM is effective and reduces subjectivity when determining the ci . Finally, with the help of the proposed VSRM, influences from chemical corrosion and confining stress on the ci and ci of the carbonate rock are analyzed. This study provides a subjective and practical method for determining σci . Moreover, it sheds light on the effects of confinement and chemical corrosion on σci