Raspberry Pi 3 Model B+ Based Endure Redicting Using Web of Things (WoT)
DOI:
https://doi.org/10.55524/Keywords:
Raspberry Pi 3 Model B+, Raspbian OS, Debian Bullseye, Temperature, Humidity, Cloud Server, Thing Speak, DHT11 Sensor, Endure Predicting, Networking, System Etiquette, SSH Etiquette, HTTP, PuTTY, VNC ViewerAbstract
The Web of Things (WoT) is a breakthrough technology that connects and controls the devices with the help of Web and make them smart and efficient. We build an WoT based Temperature and Humidity Sensing System using Raspberry Pi 3 Model B+. Endure is a vital feature in customary life, which plays a significant part in many deeds. Therefore, occasionally we need to know Endure parameter instantly. Raspberry Pi is a miniature standalone system with multiple functionalities were executed. You will interface a Digital Temperature and Humidity Sensor to receive regular updates about the Temperature and Humidity of a location remotely. The Sensor is connected to Raspberry Pi 3 Model B+, which you will program to send the readings to the Cloud Server through web, which in turn send update to Thing Speak. Thing Speak is an application platform, where the data is sent to the sever for live monitoring from anywhere in the world over web. Email notification to the user at intervals. The project deals about the Temperature and Humidity values, to read and monitor the values, using ThingSpeak system via Raspberry Pi 3 Model B+.
Downloads
References
Baladhandapani, T., & Kumar, V. V. (2017). Rasbi Cloud : Raspberry Pi. International Journal of Research in System Application and Robotics, 5(4), 1–4. https://www.ijrcar.com/Volume_5_Issue_4/v5i401.pdf
Basha, S. K. M., Chigurupati, T. R. M., & Sunil, E. (2020). The Effective Methodology for WoT Based Endure Monitoring System. International Journal of Advanced Science and Technology, 29(12), 1215–1221.
Bhuvaneshwari, S., & Nisha, A. S. A. (2014). Implementation of Tcp/Ip on Embedded Webserver using Raspberry Pi in Industrial Application. International Journal of Advanced Research in System and Communication Engineering, 3(3), 5240–5244. https://ijarcce.com/wp
content/uploads/2012/03/IJARCCE4C-s-bhuvi
IMPLEMENTATION-OF-TCP-IP.pdf
Djajadi, A., & Wijanarko, M. (2016). Ambient Environmental Quality Monitoring using WoT Sensor Network. Web Working Indonesia Journal, 8(1), 41–47. https://www.researchgate.net/publication/299184974_Ambi
ent_environmental_quality_monitoring_using_WoT_sensor _network
Girija, C., Harshalatha, H., Shires, A. G., & Pushpalatha, H. P. (2018). Web of Things (WOT) based Endure Monitoring System. International Journal of Engineering Research and Technology, 6(13). https://www.ijert.org/research/web-of
things-WoT-based-endure-monitoring-system
IJERTCONV6IS13149.pdf#:~:text=The%20system%20dea ls%20with%20monitoring,sensor%20data%20as%20graphi cal%20statistics.
Joseph, F. J. J. (2019). WoT Based Endure Monitoring System for Effective Analytics. International Journal of Engineering and Advanced Technology, 8(4), 311–315. https://doi.org/100048419/19BEIESP
Muck, P. Y., & Homam, M. J. (2018). WoT Based Endure Station Using Raspberry Pi 3. International Journal of Engineering & Technology, 7(4.30), 145–148. https://doi.org/10.14419/ijet.v7i4.30.22085
Padwal, S. C., & Kumar, M. (2016, March). Application of WSN for Environmental Monitoring in WoT Application. In S. C. Padwal & M. Kumar (Eds.), Application of WSN for Environmental Monitoring in WoT Application. International Conference on Emerging Trends in Engineering and Management Research.
Pauzi, A. F., & Hasan, M. Z. (2020). Development of WoT Based Endure Reporting System. IOP Conference Series: Materials Science and Engineering, 917(1), 012032. https://doi.org/10.1088/1757-899x/917/1/012032
Sai Ram, K. S., & Gupta, A. (2016). WoT based Data Logger System for endure monitoring using Wireless sensor networks. International Journal of Engineering Trends and Technology, 32(2), 71–75. https://doi.org/10.14445/22315381/ijett-v32p213
Satyanarayan, K. N. V., Reddy, S. R. N., Sai Teja, P. V. Y. N., & Habibuddin, M. D. B. (2016). WoT Based Smart Endure Station using Raspberry - Pi3. Journal of Chemical and Pharmaceutical Sciences. https://www.jchps.com/specialissues/2016%20SPECIAL%
ISSUE%2010/01%20JCP.pdf
Shende, V. B., Gaikwad, S. B., & Aware, V. (2020). Raspberry Pi based Endure Reporting over WoT. International Journal of Advanced Research in Electrical, Electronic and Instrumentation Engineering, 9(2), 42–51. https://doi.org/10.15662/ijareeie.2020.0902008
Shewale, S. D., & Gaiwad, S. N. (2017). An WoT Based Real- Time Endure Monitoring System using Raspberry Pi. International Journal of Advanced Research in Electrical Electronic and Instrumentation Engineering, 6(6), 4242– 4249.
https://www.ijareeie.com/upload/2017/june/9_An%20WoT %20Based%20Real
time%20endure%20monitoring%20system%20using%20R aspberry%20pi%20_1_.pdf
Soumitra, D., & Das, S. (2019). Live Endure Prediction using Raspberry Pi 3. International Journal of Advanced Technology in Engineering and Science, 7(6). https://ijates.com/images/short_pdf/1561528539_C610.pdf
Tamilarasi, B., & Saravanakumar, P. (2016). Smart Sensor Interface for Environmental Monitoring in WoT. International Journal of Advanced Research in Electronic and Communication Engineering, 5(2), 274–278. http://ijarece.org/wp-content/uploads/2016/02/IJARECE
VOL-5-ISSUE-2-274-278.pdf
Ugale, N., & Navale, M. (2016). Implementation of WoT for Environmental Condition Monitoring in Homes. International Journal for Engineering Application and Technology.
Vilayatkar, S. R., Wankhade, V. R., Wangekar, P. G., & Mundanr, N. S. (2019). WoT Based Endure Monitoring System using Raspberry Pi. International Research Journal of Engineering and Technology, 6(1), 1187–1190. https://www.irjet.net/archives/V6/i1/IRJET-V6I1220.pdf
Wallace, S., Richardson, M., & Donat, W. (2021). Getting Started With Raspberry Pi: Getting to Know the Inexpensive ARM-Powered Linux System (Make:) (4th ed.). Make Community, LLC.
S. Patibandla, M. Archana, and R. C. Tanguturi, “Object Tracking using Multi Adaptive Feature Extraction Technique,” International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 279–286, Jun. 2022, doi: 10.14445/22315381/ijett-v70i6p229.
G. Sadineni, A. M, and R. C. Tanguturi, “Optimized Detector Generation Procedure for Wireless Sensor Networks based Intrusion Detection System,” International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 63–72, Jun. 2022, doi: 10.14445/22315381/ijett
v70i6p208.
S. Patibandla, Dr. M. Archana, and Dr. R. C. Tanguturi, “DATA AGGREGATION BASED HYBRID DEEP LEARNING TECHNIQUE FOR IDENTIFYING THE UNCERTAINTIES AND ACCURATE OBJECT DETECTION,” Indian Journal of Computer Science and Engineering, vol. 13, no. 3, pp. 697–708, Jun. 2022, doi: 10.21817/indjcse/2022/v13i3/221303049.
Dr. S. R. Anand, Dr. R. C. Tanguturi, and S. D S, “Blockchain Based Packet Delivery Mechanism for WSN,” International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 2, pp. 1112–1117, Jul. 2019, doi: 10.35940/ijrte.b1627.078219.
M. V. Bharathi, R. C. Tanguturi, C. Jayakumar, and K. Selvamani, “Node capture attack in Wireless Sensor Network: A survey,” 2012 IEEE International Conference on Computational Intelligence and Computing Research, Dec. 2012, doi: 10.1109/iccic.2012.6510237