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PROTOTYPE SOCIAL INTERNET OF THINGS THROUGH CHATBOT APPLICATION IN SMART BULDING

PROTOTYPE SOCIAL INTERNET OF THINGS THROUGH CHATBOT APPLICATION IN SMART BULDING

  1. Tez No: 667384
  2. Yazar: HAJAR CHATOUI
  3. Danışmanlar: YRD. DOÇ. DR. OĞUZ ATA, Prof. Dr. HASAN HÜSEYİN BALIK, YRD. DOÇ. DR. ÇAĞATAY AYDIN
  4. Tez Türü: Yüksek Lisans
  5. Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2020
  8. Dil: İngilizce
  9. Üniversite: Altınbaş Üniversitesi
  10. Enstitü: Lisansüstü Eğitim Enstitüsü
  11. Ana Bilim Dalı: Elektrik ve Bilgisayar Ana Bilim Dalı
  12. Bilim Dalı: Elektrik ve Bilgisayar Mühendisliği Bilim Dalı
  13. Sayfa Sayısı: Belirtilmemiş.

Özet

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Özet (Çeviri)

-The ultimate purpose of the intelligent automation is to improve the potential of companies effectively. Not only it brings a series of benefits but its impact to replace the human by robots. This thesis has been focused to create intelligent automation trough the communication between sensors in this case, DH11 was used to calculated the temperature and humidity along with the low power consumption which named LoRa. The second perspective of this work is to build the virtual assistant that contains these measurements that has been saved in early stage. The bot contains multiple utterances that the builder has chosen in the next phase of study. In addition, the application was deployed in telegram due to higher security offer it. The one of the pillars, the bot implements a RASA platform the accurate infrastructure to constitute the naturel language understanding between the user and the client. The full structured was been presented in objective to introduce a clear path to create application following by the crucial steps and to mention the connection between the internet of things and social networks which named as social internet. The machine learning has been divided in two parts with 30% of the test data. The results of the chatbot has been distributed as follows: the confusion matrix, the F1-score, the accuracy for each intent. The global result in this analyze provide that F1-score is 74%, the precision is 85 % and the accuracy 75%.

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