TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic Review

Schizas, Nikolaos; Karras, Aristeidis; Karras, Christos; Sioutas, Spyros

doi:10.3390/fi14120363

Cited by 63 publications

(24 citation statements)

References 105 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, our model uses a centralized control framework, creating difficulties for its application on large-scale road networks because of high computing costs. Some emerging computer technologies, such as TinyML [61], may help to transform the model into a distributed framework, thereby further enhancing its adaptability in various traffic scenarios.…”

Section: Discussionmentioning

confidence: 99%

Reducing Red Light Running (RLR) with Adaptive Signal Control: A Case Study

Chang

2023

Electronics

View full text Add to dashboard Cite

Traffic accidents are a leading cause of premature death for citizens, with millions of injuries and fatalities occurring annually. Due to the fact that a large proportion of accidents are caused by red light running, reduction of the frequency of red light running (RLR) has been extensively researched in recent years. However, most of the previous studies have focused on reducing RLR frequency through driver education or warning sign design, with little attention paid to the relationship between RLR behavior and traffic signal control. Considering RLR is significantly affected by the number of vehicles arriving during yellow, it is possible to identify RLR behaviors in advance by analyzing data on yellow-arriving vehicles. Meanwhile, based on the strong correlation between yellow arriving and RLR frequency, it is possible to reduce RLR by traffic signal control. In this paper, we propose a quantitative model of correlation between RLR frequency and yellow light arrival based on high-resolution traffic and signal event data from Twin Cities, Minnesota. On this basis, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is implemented to find trade-offs between minimizing the RLR frequency and the traffic delay. A case study of a 6-intersection arterial road reveals that in unsaturation, saturation, and supersaturation flow, our approach can converge to a Pareto optimal front in 30–50 iterations, which shows that is possible to simultaneously reduce RLR frequency and enhance traffic efficiency safety, which is conducive to ensuring the life safety of traffic participants.

show abstract

Section: Discussionmentioning

confidence: 99%

Reducing Red Light Running (RLR) with Adaptive Signal Control: A Case Study

Chang

2023

Electronics

View full text Add to dashboard Cite

show abstract

“…al. [20]. The study was centered on the development of data processing methods and algorithms that can be quickly processed for instantaneous decisions in IoT-enabled machines.…”

Section: Related Workmentioning

confidence: 99%

A Resource-based view Assessment of Big Data Analysis and its Impact on Strategic Human Resources Quality Management Systems

K. Santhanalakshmi

2024

jier

View full text Add to dashboard Cite

This study considers the impact of big data analytic by a Resource-based view (RBV) framework on strategic HR Quality Management System (HR QMS). The study employed a mixed-method strategy to gather data of employees' performance metrics (quantitative) as well as HR professionals’ viewpoints (qualitative) through data analysis. Four machine learning algorithms, for instance Decision Trees, Random Forest, K-Means Clustering and Linear Regression were employed for the purpose of predicting and optimizing Human Resource outcomes. Study indicated the effectiveness of these algorithms in improving organizational productivity where Random Forest reached 89% correctness in predicting employee turnover and Linear Regression demonstrated a positive correlation (R-squared = 0.75) between the training hour and performance rating. Through a comparison with existing literature, the newness and relevance of the clinical data are stressed, going beyond well-known trends and into a cutting-edge analytical applications of big data analytics. The study symbolizes how big data analysis is capable of revolutionizing practices by emphasizing innovation, improving efficiencies, and learning decision making in the field of HR management.

show abstract

“…Secondly, software based on the proposed quantum RC system can be employed in ultra-low-power artificial intelligence and machine learning systems [79]. We already successfully tested our software on several mobile systems, including Raspberry Pi, and we plan to further optimise it for operation on the Arduino platform [60].…”

Section: Future Workmentioning

confidence: 99%

Reservoir Computing Using Measurement-Controlled Quantum Dynamics

Abbas,

Maksymov

2024

Electronics

View full text Add to dashboard Cite

Physical reservoir computing (RC) is a machine learning algorithm that employs the dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this paper, we introduce a quantum RC system that employs the dynamics of a probed atom in a cavity. The atom experiences coherent driving at a particular rate, leading to a measurement-controlled quantum evolution. The proposed quantum reservoir can make fast and reliable forecasts using a small number of artificial neurons compared with the traditional RC algorithm. We theoretically validate the operation of the reservoir, demonstrating its potential to be used in error-tolerant applications, where approximate computing approaches may be used to make feasible forecasts in conditions of limited computational and energy resources.

show abstract

TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic Review

Cited by 63 publications

References 105 publications

Reducing Red Light Running (RLR) with Adaptive Signal Control: A Case Study

Reducing Red Light Running (RLR) with Adaptive Signal Control: A Case Study

A Resource-based view Assessment of Big Data Analysis and its Impact on Strategic Human Resources Quality Management Systems

Reservoir Computing Using Measurement-Controlled Quantum Dynamics

Contact Info

Product

Resources

About