Sage Journals: Discover world-class research

Abstract

There are many optional basic frameworks of the Internet of Things, which result in high energy consumption for Internet of Things monitoring platform of straw recycling, and cannot improve the thermal energy conversion rate of the straw recycling monitoring system effectively. Thus, the design is based on smart surveillance system of Internet of things of straw recycling process. The WMNBM14s chip and the STM32F103 chip are used in the basic frame of Internet of things to collect and process the straw recycling data in the monitoring system, and obtain the data processing result of the straw recycling process. The data processing result of the straw recycling process is transmitted to Internet of Things Control Terminal through the BCM43362 wireless chip. The experimental results show that the designed platform has low energy consumption and can improve the thermal energy conversion rate of the straw recovery system.

Keywords

Genetic algorithm straw recycling process Internet of Things monitoring system BCM43362

Get full access to this article

View all access options for this article.

References

Wang

, Geng

, Fan

, et al., An Immune Genetic Algorithm for Multi-Echelon Inventory Cost Control of IOT Based Supply Chains[J], IEEE Access 52 (2018), 112–115.

Deng

, Peng

et al., An Intelligent Outlier Detection Method with One Class Support Tucker Machine and Genetic Algorithm towards Big Sensor Data in Internet of Things[J], IEEE Transactions on Industrial Electronics 85 (2018), 10–19.

Martins

J.A.

, Mazayev

, Correia

et al., GACN: Self-clustering Genetic Algorithm for Constrained Networks[J], IEEE Communications Letters 32 (2016), 148–155.

Gai

, Qiu

, Hui

Cost-Aware Multimedia Data Allocation for Heterogeneous Memory Using Genetic Algorithm in Cloud Computing[J], IEEE Transactions on Cloud Computing 63 (2016), 252–259.

Muhammad

, Saxena

, Qureshi

I.M.

et al., Hybrid Artificial Bee Colony Algorithm for an Energy Efficient Internet of Things based on Wireless Sensor Network[J], Iete Technical Review 34 (2017), 39–51.

Ren

, Yang

, Wu

et al., An Effective Multi-Objective Optimization Algorithm for Spectrum Allocations in the Cognitive-Radio-Based Internet of Things[J], IEEE Access 47 (2018), 55–63.

Luo

Q.K.

, Wu

J.F.

, Yang

et al., Multi-objective optimization of long-term groundwater monitoring network design using a probabilistic Pareto genetic algorithm under uncertainty[J], Journal of Hydrology 534 (2016), 352–363.

Shen

, Han

, Ling

et al., Dynamic Generation of Internet of Things Organizational Structures through Evolutionary Computing[J], IEEE Internet of Things Journal 44 (2018), 968–977.

Research on smart surveillance system of Internet of Things of straw recycling process based on optimizing genetic algorithm

Abstract

Keywords

Get full access to this article

References