An Internet-of-Things (IoT) System to Automate the Pet Door Controlling using Artificial Intelligence and Computer Vision

2021 ◽  
Author(s):  
Alex Lin ◽  
Yu Sun
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Internet Of Things ◽  
Smart Home ◽  
Living Condition ◽  
Home Systems

Pets are cute and fun, but sometimes it gets annoying when you are trying to get some sleep in [14]. Also the population of people who would like to be accompanied by pets is rising rapidly. However, people these days lack time to meet all requirements of pets, which causes plenty of tragedies [3]. In this paper, we designed an application/tool called Automate the Pet Door Controlling which is using artificial intelligence and Computer vision to create a better living condition for pets, and a easier life for people who love their pets, especially for those who cannot spend a lot of time or physically hard to open doors for pets. My design builds an integratable system which is available for most smart home systems, also this design supports extra datasets imported to enlarge the types of pets.

scholarly journals Security Vulnerability Assessment of Google Home Connection with an Internet of Things Device

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 1
Author(s):  
Hilal Çepik ◽  
Ömer Aydın ◽  
Gökhan Dalkılıç
Keyword(s):  
Internet Of Things ◽  
Vulnerability Assessment ◽  
Smart Home ◽  
Human Life ◽  
Computer Systems ◽  
Security Vulnerability ◽  
Network Time ◽  
Network Time Protocol ◽  
Home Systems

With virtual assistants, both changes and serious conveniences are provided in human life. For this reason, the use of virtual assistants is increasing. The virtual assistant software has started to be produced as separate devices as well as working on phones, tablets, and computer systems. Google Home is one of these devices. Google Home can work integrated with smart home systems and various Internet of Things devices. The security of these systems is an important issue. As a result of attackers taking over these systems, very serious problems may occur. It is very important to take the necessary actions to detect these problems and to take the necessary measures to prevent possible attacks. The purpose of this study is to test whether an attack that attackers can make to these systems via network time protocol will be successful or not. Accordingly, it has been tried to attack the wireless connection established between Google Home and an Internet of Things device over the network time protocol. Attack results have been shared.

scholarly journals A deep learning platooning-based video information-sharing Internet of Things framework for autonomous driving systems

2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988313 ◽  
Author(s):  
Zishuo Zhou ◽  
Zahid Akhtar ◽  
Ka Lok Man ◽  
Kamran Siddique
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Deep Learning ◽  
Internet Of Things ◽  
Information Sharing ◽  
Communication Technology ◽  
Empirical Evaluation ◽  
Traffic Lights ◽  
Video Information ◽  
Safety And Stability

To enhance the safety and stability of autonomous vehicles, we present a deep learning platooning-based video information-sharing Internet of Things framework in this study. The proposed Internet of Things framework incorporates concepts and mechanisms from several domains of computer science, such as computer vision, artificial intelligence, sensor technology, and communication technology. The information captured by camera, such as road edges, traffic lights, and zebra lines, is highlighted using computer vision. The semantics of highlighted information is recognized by artificial intelligence. Sensors provide information on the direction and distance of obstacles, as well as their speed and moving direction. The communication technology is applied to share the information among the vehicles. Since vehicles have high probability to encounter accidents in congested locations, the proposed system enables vehicles to perform self-positioning with other vehicles in a certain range to reinforce their safety and stability. The empirical evaluation shows the viability and efficacy of the proposed system in such situations. Moreover, the collision time is decreased considerably compared with that when using traditional systems.

scholarly journals A Systematic Content Review of Artificial Intelligence and the Internet of Things Applications in Smart Home

2020 ◽  
Vol 10 (9) ◽  
pp. 3074 ◽  
Author(s):  
Samad Sepasgozar ◽  
Reyhaneh Karimi ◽  
Leila Farahzadi ◽  
Farimah Moezzi ◽  
Sara Shirowzhan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart Home ◽  
Smart Homes ◽  
Research Direction ◽  
The Internet ◽  
Main Question ◽  
Smart Energy Systems ◽  
Assistive Systems ◽  
The Internet Of Things

This article reviewed the state-of-the-art applications of the Internet of things (IoT) technology applied in homes for making them smart, automated, and digitalized in many respects. The literature presented various applications, systems, or methods and reported the results of using IoT, artificial intelligence (AI), and geographic information system (GIS) at homes. Because the technology has been advancing and users are experiencing IoT boom for smart built environment applications, especially smart homes and smart energy systems, it is necessary to identify the gaps, relation between current methods, and provide a coherent instruction of the whole process of designing smart homes. This article reviewed relevant papers within databases, such as Scopus, including journal papers published in between 2010 and 2019. These papers were then analyzed in terms of bibliography and content to identify more related systems, practices, and contributors. A designed systematic review method was used to identify and select the relevant papers, which were then reviewed for their content by means of coding. The presented systematic critical review focuses on systems developed and technologies used for smart homes. The main question is ”What has been learned from a decade trailing smart system developments in different fields?”. We found that there is a considerable gap in the integration of AI and IoT and the use of geospatial data in smart home development. It was also found that there is a large gap in the literature in terms of limited integrated systems for energy efficiency and aged care system development. This article would enable researchers and professionals to fully understand those gaps in IoT-based environments and suggest ways to fill the gaps while designing smart homes where users have a higher level of thermal comfort while saving energy and greenhouse gas emissions. This article also raised new challenging questions on how IoT and existing developed systems could be improved and be further developed to address other issues of energy saving, which can steer the research direction to full smart systems. This would significantly help to design fully automated assistive systems to improve quality of life and decrease energy consumption.

Artificial Intelligence and Machine Learning Algorithms

2020 ◽  
pp. 188-219
Author(s):  
Amit Kumar Tyagi ◽  
Poonam Chahal
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Learning Techniques

With the recent development in technologies and integration of millions of internet of things devices, a lot of data is being generated every day (known as Big Data). This is required to improve the growth of several organizations or in applications like e-healthcare, etc. Also, we are entering into an era of smart world, where robotics is going to take place in most of the applications (to solve the world's problems). Implementing robotics in applications like medical, automobile, etc. is an aim/goal of computer vision. Computer vision (CV) is fulfilled by several components like artificial intelligence (AI), machine learning (ML), and deep learning (DL). Here, machine learning and deep learning techniques/algorithms are used to analyze Big Data. Today's various organizations like Google, Facebook, etc. are using ML techniques to search particular data or recommend any post. Hence, the requirement of a computer vision is fulfilled through these three terms: AI, ML, and DL.

scholarly journals ForeSight - AI-based Smart Living Platform Approach

2020 ◽  
Vol 6 (3) ◽  
pp. 384-387
Author(s):  
Jochen Bauer ◽  
Michael Hechtel ◽  
Christoph Konrad ◽  
Martin Holzwarth ◽  
Andreas Mayr ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart Home ◽  
Service Providers ◽  
Daily Life ◽  
The Internet ◽  
Context Sensitive ◽  
Smart Living ◽  
Housing Industry ◽  
The Internet Of Things

AbstractIn the upcoming years, the internet of things (IoT) will enrich daily life. The combination of artificial intelligence (AI) and highly interoperable systems will bring contextsensitive multi-domain services to reality. This paper describes a concept for an AI-based smart living platform with open- HAB, a smart home middleware, andWeb of Things (WoT) as key components of our approach. The platform concept considers different stakeholders, i.e. the housing industry, service providers, and tenants. These activities are part of the Fore- Sight project, an AI-driven, context-sensitive smart living platform.

scholarly journals IMPROVEMENT OF SCIENCE AND TECHNOLOGY THROUGH INTERNET OF THINGS (IOT) FOR SMART HOME APPLICATION TRAINING FOR STUDENTS OF SMK NURUL JADID PROBOLINGGO

2021 ◽  
Vol 5 (2) ◽  
pp. 274
Author(s):  
Amalia Herlina ◽  
Ahmad Daviatu Firdausi ◽  
Sulhan Maulana Akmal Habibi ◽  
Virgan Dirgantara
Keyword(s):  
Internet Of Things ◽  
21St Century ◽  
Smart Home ◽  
Industrial Revolution ◽  
Science And Technology ◽  
Test Method ◽  
Entire Group ◽  
Post Test ◽  
Internet Of Thing ◽  
Home Systems

                                                         AbstractThe advancement of science and technology in the era of the Industrial Revolution 4.0 is developing rapidly, including the development of the Internet of Things (IoT) which makes the world smarter. An example of its implementation is the smart home system which offers advantages, so that it is currently being widely socialized in Indonesian society. This training aims to provide solutions to partner problems, namely SMK Nurul Jadid, especially Grade 12 students. There are two main problems with partners that have a high level of urgency to be resolved, namely improving science and technology, and developing 21st century competence for students. The series of activities carried out included 1) Making IoT learning media for smart home systems, 2) Learning about IoT and smart home systems, 3) Training on making smart home designs, 4) Training on assembling smart home system tools, 5) Training on the use of the Blynk Application for smart home control system 6) Development of 21st century competence (digital era literacy, effective communication, inventive thinking, and high productivity). Activity achievement is measured using the before after test (pre-test and post-test) method. From the increasing number of correct answers in the post-test, it is known that there is an increase in students' understanding of science and technology about IoT for smart home systems. Meanwhile, the achievement of 21st century competency development is measured by the value of case studies given to students in which the entire group of students achieves the predicate of GOOD. The implementation of all training activities went well. The results of the evaluation questionnaire stated that students felt that this training was very beneficial for improving science and technology and also very beneficial for the development of their competencies. Thus, this series of activities is a solution because it can solve internal problems as well as solutions to external problems of partners.Keywords: BLYNK IoT Platforms, Internet of Thing, Smart Home System, Vocational High School                                                            AbstrakKemajuan IPTEK di era Revolusi Industri 4.0 berkembang pesat dan cepat, termasuk perkembangan Internet of Things (IoT) yang membuat dunia lebih pintar. Contoh implementasinya adalah sistem smart home yang menawarkan keunggulan, sehingga saat ini mulai banyak disosialisasikan di masyarakat Indonesia. Pelatihan ini bertujuan untuk memberikan solusi permasalahan mitra yaitu SMK Nurul Jadid khususnya siswa Kelas 12. Terdapat dua permasalahan utama mitra yang memiliki tingkat urgensi tinggi untuk diselesaikan, yaitu peningkatan IPTEK dan pengembangan kompetensi abad 21 bagi siswa. Rangkaian kegiatan yang dilakukan meliputi 1) Pembuatan media pembelajaran IoT untuk sistem smart home, 2) Pembelajaran tentang IoT dan sistem  smart home, 3) Pelatihan pembuatan desain smart home, 4) Pelatihan perakitan  alat sistem  smart home 5) Pelatihan penggunaan Aplikasi Blynk untuk sistem kontrol smart home 6) Pengembangan kompetensi abad 21 (literasi era digital, komunikasi efektif, berpikir inventif dan produktivitas tinggi). Capaian kegiatan diukur menggunakan metode tes before after (pre-test dan post-test). Dari jumlah jawaban benar yang meningkat pada post-test, diketahui adanya peningkatan pemahaman siswa terhadap IPTEK tentang IoT untuk sistem smart home. Sedangkan pencapaian pengembangan kompetensi abad 21 diukur dari nilai studi kasus yang diberikan pada siswa yang mana seluruh kelompok siswa mencapai predikat BAIK. Pelaksanaan seluruh kegiatan pelatihan berlangsung dengan baik. Hasil kuesioner evaluasi menyebutkan, siswa merasakan bahwa pelatihan ini sangat bermanfaat bagi peningkatan IPTEK dan juga sangat bermanfaat bagi pengembangan kompetensi mereka. Dengan demikian, rangkaian kegiatan ini merupakan solusi karena dapat menyelesaikan permasalahan internal sekaligus solusi permasalahan eksternal mitra.Kata kunci: Aplikasi BLYNK, Internet of Thing, Sekolah Menengah  Kejuruan, Smart Home System

scholarly journals An Approach to Share Self-Taught Knowledge between Home IoT Devices at the Edge

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 833 ◽  
Author(s):  
Ingook Jang ◽  
Donghun Lee ◽  
Jinchul Choi ◽  
Youngsung Son
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Power Consumption ◽  
Response Time ◽  
Knowledge Sharing ◽  
Smart Home ◽  
Artificial Intelligence Techniques ◽  
Iot Applications ◽  
Iot Devices

The traditional Internet of Things (IoT) paradigm has evolved towards intelligent IoT applications which exploit knowledge produced by IoT devices using artificial intelligence techniques. Knowledge sharing between IoT devices is a challenging issue in this trend. In this paper, we propose a Knowledge of Things (KoT) framework which enables sharing self-taught knowledge between IoT devices which require similar or identical knowledge without help from the cloud. The proposed KoT framework allows an IoT device to effectively produce, cumulate, and share its self-taught knowledge with other devices at the edge in the vicinity. This framework can alleviate behavioral repetition in users and computational redundancy in systems in intelligent IoT applications. To demonstrate the feasibility of the proposed concept, we examine a smart home case study and build a prototype of the KoT framework-based smart home system. Experimental results show that the proposed KoT framework reduces the response time to use intelligent IoT devices from a user’s perspective and the power consumption for compuation from a system’s perspective.

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