Recently updated on: 2020-01-06
Research on the Key Problems of Solar Insecticidal Lamp Internet of Things
Along with the increasing awareness of environmental protection and growing demand for green and pollution-free agricultural products, it has a great need to explore new ways to apply greener pest control methods in agricultural production. Researching on Solar Insecticidal Lamps (SILs) has continuously received incremental attentions from both the academia and industry, which brings a new mode for the preventing and controlling of agricultural migratory pests with phototaxis feature, and now is becoming to a hot research topic. Towards the fast development of “precision agriculture” and “smart agriculture” as well as the increasing demands for agricultural informatization, Wireless Sensor Networks (WSNs) have been widely used for agricultural information collection and intelligent control of agricultural equipment. WSNs are suitable for large-scale deployment and regional monitoring, which can be easily combined with SIL nodes. Based on the combination, a new type of agricultural Internet of things – Solar Insecticidal Lamps Internet of Things (SIL-IoTs) was proposed and the technology of WSNs for the prevention and control of phototactic migratory pests in agricultural applications were surveyed.
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Research on Photovoltaic Agricultural Internet of Things
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Research on application of Mobile Crowd Sensing for Data Collection towards Smart Agriculture
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Comparative analysis between SAGIN and i-SAGIN. The black textbox signifies SAGIN that is only used in in-production phase, and the red textbox signifies i-SAGIN that can be used in entire process of agricultural production.
Research on Fault Diagnosis of Industrial Networks and Equipment
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Research on Core Problems of High Precision Industrial Noise Map Based on Group Intelligence Perception
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Intelligent Detection of Toxic Gases in Petrochemical Enterprises Based on Wireless Sensor Networks
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a) The illustration of RNG [6] — the edge e(u, v) is only eliminated from the graph if a vertex w exists within intersection region of both u and v; b) the illustration of GG [7] — the edge e(u, v) is only eliminated from the graph if a vertex w exists within the circle with diameter d(u, v); c) an example of full graph of a WSN using NetTopo3 simulator; d) the RNG; e) the GG subset of the full graph
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Illustration of the proposed scheme, DeGas, to detect boundary area of the invisible toxic gas.
Academic StaffResearch on Key Problems of Cooperative Sleep Scheduling in Industrial Wireless Sensor Networks
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Example of a group-based IWSN with three groups of sensor nodes and six C-nodes (critical node). If these critical nodes cannot get opportunities to sleep to save energy, it can easily cause a network isolation problem in the network.
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Neighbor nodes’ death speedup problem illustration. Blue nodes are normal working nodes, green nodes are sleeping nodes, red nodes are alwaysawake nodes, and black nodes are dead nodes.
Research on DV-based Localization Algorithms in the Wireless Sensor Networks with Duty-cycled and Radio Irregular Sensors
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Research on Heterogeneous Intelligent Network Integrated Monitoring Platform in Large Petrochemical Enterprises
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Impact of radio irregularity on awake node in the CKN-based sleep scheduling with a network size 600×600 m2 and N = 400 deployed nodes. We use a WSN simulator NetTopo.3 (a) Without link asymmetry, (b)-(c) The number of awake node is increased to 40% link asymmetry compared with 20% link asymmetry with same number of irregular nodes. (d)-(f) Moreover, the number of awake node increases to maintain higher k-connectivity in presence of link asymmetry with irregular nodes. Almost all the sensor nodes are always-on with high k-value, i.e., k = 4.
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Lifetime with probability of asymmetric node and different link asymmetry in CKN-based sleep scheduling.
NetTopo: A framework of simulation and visualization for wireless sensor networks
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Internet of Things for Environmental Noise Mapping in Smart Cities
With the rapid development of modern society, the negative effects of noise pollution on public health, animal and plants growth are exacerbated, that seriously hinder the sustainable development of ecological environment. To obtain detailed noise distribution information, many countries have launched the noise mapping strategic action. The academics have made great contributions for real-time noise data acquisition in terms of low cost sensor node design, system architecture and binary noise determination. However, there are still many open research issues that need to be addressed, such as high sensing energy consumption, resource constraint on sensor nodes and lossy wireless networks. This project focuses on the challenges of environmental sampling, processing and wireless transmission during noise data acquisition with low cost wireless sensor networks to achieve adaptive noise sampling, noise sources recognition on resource-constrained embedded platforms, and reliability improvement of wireless sound data delivery.
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