a smart building system integrated with an edge computing

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A Smart Building System Integrated with An Edge Computing Algorithm and IoT Mesh Networks Archit Gajjar and Xiaokun Yang Department of Engineering, University of Houston, Clear Lake Introduction Analysis & Feedback Algorithm Use Cases Data processing & Analysis A smart building system integrated with the emerging edge computing technology and IoT Mesh networks: First we fabricated 4 IoT Mesh Boards using the CSRmesh solution Second we established a mesh network with one IoT host/server and three devices. (The BLE mesh technology is not standardized yet, only a few venters provide such solutions. ) The next step is to develop the data analysis algorithm at the network edge and to connect to the GoKit cloud service with a GizWits V3.0 board. . Smart Building - We plan to setup this prototype in our college campus building. A personal computer will be used as an edge server to connect with both the IoT host and the GizWits board. The IoT host is in charge of the IoT network monitor and control, and the GizWits board is adopted to connect to the GoKit cloud. Smart Agriculture - System contains humidity, temperature, and light sensors, agriculture filed thus can have the best out of it along with the algorithm, which can let system work totally autonomous and take most efficient decisions. All the calculation and execution is done by system and there is no human interruption. Algorithm has five different phases. Fetching data through sensors – To gather data information with sensor networks. Data processing & Analysis Autonomous decision execution Process will be executed automatically without human interruption, based on the previous phase analysis. Feedback controller – Data transferred to Data processing & Analysis phase to complete concurrent and iterative process, if necessary. System neutralization – System will be neutralized when system no longer requires process execution but data fetching and processing will not be stopped. So far we have successfully, created IoT mesh network with sensors and host / server module. We were also able to gather the data information from the sensor network. Conclusion and Future Work cloud-edge-IoT System Architecture After fetching data different measurement will be carefully observed in this phase like frequent data fluctuation, steady data information, garbage values etc. There will be three categories to process data based on time sensitiveness. Most time sensitive data are priority and will be executed first by all means. A bit less sensitive data which can wait a bit and will be communicated to edge computation part and rest of the process will be handled over there. The last category will be the one where data does not require to be processed immediately, which can wait for some time, will be sent to data server. In the case, when such data is required, it will be processed followed by restore the data to data server after completion of process. The System Architecture can be split into three stages. IoT Mesh Network – One host / server is wirelessly connected with three devices using the CSRmesh Technology. Edge Node – Edge node is implemented between cloud server and IoT mesh network which contains data analysis & feedback algorithms. Cloud Server – Host/server is connected to external GoKit cloud server with GizWits V3.0 to keep data like sensor readings and feedback control the IoT network. The system will show an effective solution to smart home/building with proposing a cloud-edge-IoT system, and fundamentally extending the connection area to cover an entire farm or factory. To show our efforts, we also developed a web page (sceweb.sce.uhcl.edu/Xiaokun -> FC) where valuable information will be visible and project demo will be visual too. Our future work will focus on developing the edge computing algorithms and connecting to the Gokit cloud service using the GizWits V3.0 board. (a) CSRmesh Host/Server (b) Humidity/Thermal Sensor (c) Motor Board (d) LED Switch (e) CAplix BLM mesh Model: JM1L2S (g) High Torque Stepper Motor-24BYJ48) f) AN2302 Sensor (g) Optical Power LED (h) GizWits V3.0 board Fig. 4 A CSRmesh demo on UHCL campus Fig. 3 Algorithm flow chart Fig. 1 Sensor reading test bench Fig. 2 Cloud-fog-IoT system architecture

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A Smart Building System Integrated with An Edge Computing Algorithm and IoT Mesh Networks

Archit Gajjar and Xiaokun Yang

Department of Engineering, University of Houston, Clear Lake

Introduction Analysis & Feedback Algorithm

Use Cases

Data processing & Analysis

A smart building system integrated with the emerging edgecomputing technology and IoT Mesh networks:

First we fabricated 4 IoT Mesh Boards using the CSRmesh solution

Second we established a mesh network with one IoT host/server andthree devices. (The BLE mesh technology is not standardized yet, only afew venters provide such solutions. )

The next step is to develop the data analysis algorithm at the networkedge and to connect to the GoKit cloud service with a GizWits V3.0 board.

.

Smart Building - We plan to setup this prototype in our collegecampus building. A personal computer will be used as an edgeserver to connect with both the IoT host and the GizWits board.The IoT host is in charge of the IoT network monitor and control,and the GizWits board is adopted to connect to the GoKit cloud.

Smart Agriculture - System contains humidity, temperature,and light sensors, agriculture filed thus can have the best out of italong with the algorithm, which can let system work totallyautonomous and take most efficient decisions. All the calculationand execution is done by system and there is no humaninterruption.

Algorithm has five different phases.

Fetching data through sensors – To gather data information withsensor networks.

Data processing & Analysis

Autonomous decision execution – Process will be executedautomatically without human interruption, based on the previous phaseanalysis.

Feedback controller – Data transferred to Data processing & Analysisphase to complete concurrent and iterative process, if necessary.

System neutralization – System will be neutralized when system nolonger requires process execution but data fetching and processing willnot be stopped.

So far we have successfully, created IoT mesh network withsensors and host / server module. We were also able to gatherthe data information from the sensor network.

Conclusion and Future Work

cloud-edge-IoT System Architecture

After fetching data different measurement will be carefullyobserved in this phase like frequent data fluctuation, steady datainformation, garbage values etc. There will be three categories toprocess data based on time sensitiveness.

Most time sensitive data are priority and will be executed first by allmeans.

A bit less sensitive data which can wait a bit and will be communicatedto edge computation part and rest of the process will be handled overthere.

The last category will be the one where data does not require to beprocessed immediately, which can wait for some time, will be sent todata server. In the case, when such data is required, it will be processedfollowed by restore the data to data server after completion of process.

The System Architecture can be split into three stages.

IoT Mesh Network – One host / server is wirelessly connected withthree devices using the CSRmesh Technology.

Edge Node – Edge node is implemented between cloud server and IoTmesh network which contains data analysis & feedback algorithms.

Cloud Server – Host/server is connected to external GoKit cloudserver with GizWits V3.0 to keep data like sensor readings and feedbackcontrol the IoT network.

The system will show an effective solution to smart home/buildingwith proposing a cloud-edge-IoT system, and fundamentallyextending the connection area to cover an entire farm or factory.

To show our efforts, we also developed a web page(sceweb.sce.uhcl.edu/Xiaokun -> FC) where valuableinformation will be visible and project demo will be visual too.

Our future work will focus on developing theedge computing algorithms and connectingto the Gokit cloud service using the GizWitsV3.0 board.

(a) CSRmesh Host/Server (b) Humidity/Thermal Sensor

(c) Motor Board (d) LED Switch

(e) CAplix BLM mesh Model: JM1L2S

(g) High Torque Stepper Motor-24BYJ48)

f) AN2302 Sensor

(g) Optical Power LED

(h) GizWits V3.0 board

Fig. 4 A CSRmesh demo on UHCL campus

Fig. 3 Algorithm flow chart

Fig. 1 Sensor reading test bench

Fig. 2 Cloud-fog-IoT system architecture