Internet Of Things
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2022 ◽  
Vol 16 (1) ◽  
pp. 0-0

The rise of the Internet of Things (IoT) has driven mobile applications development. As a result, in the consumer IoT (CIoT) space, any product usually comes with a smartphone application to either control, programme, or just view what is happening with the product. The IoT brings with it opportunities and challenges to consumers. For example, IoT technology makes it possible to connect all of a person’s devices to create a smart eco-system or assemblage. However, the biggest threat in CIoT is personal data security. This study utilized a qualitative narrative inquiry and Delphi technique to explore data security issues that come with CIoT assemblages and associated mobile applications in South Africa. The study established that consumers enjoy the convenience and benefits that IoT technology brings. It is concluded that for CIoT to thrive, safety is crucial, and all the stakeholders in the IoT assemblage need to ensure the protection of consumers.


2022 ◽  
Vol 3 (1) ◽  
pp. 1-30
Author(s):  
Ajay Krishna ◽  
Michel Le Pallec ◽  
Radu Mateescu ◽  
Gwen Salaün

Consumer Internet of Things (IoT) applications are largely built through end-user programming in the form of event-action rules. Although end-user tools help simplify the building of IoT applications to a large extent, there are still challenges in developing expressive applications in a simple yet correct fashion. In this context, we propose a formal development framework based on the Web of Things specification. An application is defined using a composition language that allows users to compose the basic event-action rules to express complex scenarios. It is transformed into a formal specification that serves as the input for formal analysis, where the application is checked for functional and quantitative properties at design time using model checking techniques. Once the application is validated, it can be deployed and the rules are executed following the composition language semantics. We have implemented these proposals in a tool built on top of the Mozilla WebThings platform. The steps from design to deployment were validated on real-world applications.


Author(s):  
Tharun Palla

Abstract: With rapid growth in personal luxury and increasing jobs, People are comfortable using their personal vehicles rather than public transport to fulfill their transportation needs. This is because of ease of access and feasibility to use the vehicles at their own will at any point of time. It is leading to heavy traffic congestions and long waiting periods at traffic signals which is becoming a heavy burden in all major cities and will be affecting environment because of pollution caused by so many vehicles and also will disturb the individual’s time schedule. This paper proposes a system using data analytics, machine learning algorithms, Internet of things to predict the traffic flow, generate precise data about real time traffic congestions at that instant and rerouting the vehicles using navigation through a less congested path ultimately developing an Intelligent Traffic Management system. The architecture of the system is based on image analysis of vehicles using cameras at signals, using GPS in mobiles to monitor traffic in particular route. The combination of these two can be used to generate useful data about traffic congestions. Next part is calculating the efficient path to reach the destination with the generated data to minimize traffic and reach destination short period of time. The generated efficient route and traffic intensity is updated to the user with the help of maps application. Keywords: data analytics, machine learning, GPS, image analysis, intelligent traffic management system, Internet of things


Author(s):  
Srutanjay Ramesh

Abstract: In this paper, an autonomous Mars Rover is designed using the software SOLIDWORKS and a mechanical model is developed with in-depth simulations to analyse the functions of the vehicle. Furthermore, a graphical user interface is also developed based on the principles of Internet of Things using Node-Red to control and monitor the rover remotely. The red planet, i.e.; Mars, has been the centre of attraction for over 2 decades now, with astrophysicists and engineers working in unison to build devices and launch shuttle programs to understand and learn about the planet and gather more intelligence. This paper proposes the detailed development of a 6-wheeled rover that could explore the terrains of Mars, featuring a stereo vision system that could provide live video coverage and a robotic arm that can facilitate investigation of the surface, in an attempt to contribute to and fulfil the human race’s mission to Mars. It employs multiple onboard sensors that can acquire necessary data pertaining to the environmental conditions and actuators that enable functionality, with the sensors and actuators integrated onto a control system based on microcontrollers and microprocessors such as Arduino and Raspberry Pi. The rover also has a provision of a payload bay in its rear which enables it to carry loads. The SOLIDWORKS tool from Dassault systèmes is used to design and model the rover and carry out static analysis and motion studies. The GUI developed in the further sections allows overall voice control for the user and makes the task of monitoring the rover a much simpler task by eliminating the complexity that rises due to multiple control platforms. Keywords: Mars Rover, Graphical User Interface (GUI), Chassis, Mastcam, Actuators, Internet of Things (IoT), Nitinol, Payload


2022 ◽  
Vol 32 (1) ◽  
pp. 429-439
Author(s):  
Lili Sun ◽  
Hairui Sun ◽  
Ning Cao ◽  
Xiuli Han ◽  
Guangsheng Cao ◽  
...  
Keyword(s):  

2021 ◽  
pp. 1-10
Author(s):  
Rhuanito Soranz Ferrarezi ◽  
Tzu Wei Peng

Precision agriculture involves applying artificial intelligence, computers, sensors, and automation to improve crop field productivity while monitoring environmental conditions to conserve soil, water, and other natural resources focusing on agricultural sustainability. Despite many applications in agriculture, data monitoring and recording technologies have limited use due to the price. Low-cost open-source systems, like the ones available with the Internet of things (IoT) world, can potentially be developed as a universal-fit and cloud-connected technology for multiple applications. We designed and built a basic data collecting system using a commercial standalone embedded computer with Python programming language, serial data interface (SDI)-12/analog sensor adaptor, and digital sensors to monitor soil moisture and transmit the data remotely. SDI-12 is a standard communication protocol that transfers digital sensor measurements to a data recorder. We set up a pilot study that automatically collected and uploaded the data into the Internet to allow remote data transfer and access. The system performed reliably over 1 week with potting soil under field conditions without maintenance and successfully recorded data in real-time. The volumetric water content ranged from 0.03 to 0.23 m3·m−3, dielectric permittivity from 3.3 to 18.9 (unitless), EC from 0.0 to 0.3 dS·m−1, and soil temperature from 20.7 to 44.8 °C. All the data were successfully collected and uploaded to the cloud every 20 min, allowing users to remotely monitor the data using a free online application. However, heavy rainfall and high insolation could damage the system through excessive moisture or overheating, requiring a waterproof and heavy-duty protection case. The ThingSpeak channel allows customizing to suit a user’s specific requirements or adding more features for further development, such as automated irrigation, which can improve irrigation and fertilization efficiency by applying water and fertilizers at the right time based on sensor readings.


2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Shuaiqi Wang

With the continuous development of artificial intelligence technology, the supply chain logistics industry has shown new changes. The products of the intelligent era such as smart devices, big data computing, and Internet of Things technology have gradually become the transformation and innovation of logistics and supply chain enterprises. The important driving force of the logistics and supply chain industry will greatly improve the operational efficiency of the logistics and supply chain industry. Methods. This article studies the technical framework of artificial intelligence and explores the upgrading and transformation of supply chain logistics enterprises in logistics infrastructure, production tools, and logistics operation processes under the promotion of artificial intelligence technology, from warehouse location, inventory management, warehousing operations, transportation, and distribution. The data analysis and prediction analyze the impact of artificial intelligence on the supply chain logistics field and finally point out the problems in the intelligent development of the supply chain logistics field and put forward targeted suggestions to promote the modern supply chain logistics to become more intelligent. developThe new development trend of smart logistics is towards sharing economy, automation, service efficiency, and cost reduction. Results. In this context, if logistics companies want to achieve higher-quality development, they cannot do without business model innovation and larger-scale collaboration, transparency of logistics information, and more comprehensive information sharing. The new trend of the development of smart logistics is to develop in the direction of sharing economy, automation, service efficiency, and cost reduction. Conclusion. Intelligence and the Internet of Things are the inevitable trend of the development of smart logistics, which is mainly realized through the Internet of Things path in terms of visual information technology, intelligent robot operation, vehicle scheduling, and cargo traceability.


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