As deep neural networks (DNNs) continue their reach into a wide range of application domains, the neural network architecture of DNN models becomes an increasingly sensitive subject, due to either intellectual propert...
详细信息
Meat and dairy products are negatively impacted by a lack of technology in the livestock industry in developing countries. To cater for this challenge, the Internet of Things (IoT), Node-MCU, and intelligent wireless ...
详细信息
ISBN:
(数字)9781665461221
ISBN:
(纸本)9781665461238
Meat and dairy products are negatively impacted by a lack of technology in the livestock industry in developing countries. To cater for this challenge, the Internet of Things (IoT), Node-MCU, and intelligent wireless sensor nodes are deployed to create a new smart dairy monitoring system. A cow collar with a temperature sensor, a GPS module, and an environmental parameter regularization system are included. Data from modules is stored in a separate database using an innovative IoT -based front end. All the deployed WS nodes can determine whether the environment is stable or not at any given time. Sensors built inside cow collars can assess vital indications like temperature and pulse rate, as well as the animal's exact location. The design of the Cow collar also has a feature that automatically alerts the owner. The plug-and-play technology offered is designed to be easy to adapt. When a farm has many animals, automation decreases the need for human involvement and so lowers labor expenses. The exploitation of remote monitoring systems improves the health of the animals and hence yields a better amount of dairy. This study also includes a detailed comparison of the proposed implementation with current systems to demonstrate its originality. Other applications, such as smart monitoring of zoo animals and poultry, may be derived from the proposed technology.
The Platform for Long-lasting Observation of Marine Ecosystems (PLOME) project aims to improve the communication capabilities of stand-alone seafloor platforms for monitoring marine ecosystems. PLOME project involves ...
The Platform for Long-lasting Observation of Marine Ecosystems (PLOME) project aims to improve the communication capabilities of stand-alone seafloor platforms for monitoring marine ecosystems. PLOME project involves building a cooperative network that integrates several seafloor remote stations with AUVs and USVs to collect and transmit the data. One of the innovative ideas studied in PLOME is the integration of pop-up buoys with sensing, processing, and communication capabilities. These buoys are periodically released untethered from the seafloor node with part of its collected data, and become oceanic drifters that transmit this data and their position using a satellite link. This article describes the design of the pop-up project and discusses the technological challenges related to wireless underwater communication, automatic release systems, and robust satellite communication links. Preliminary tests demonstrate the feasibility of the project's implementation.
We live in a world where ubiquitous systems surround us in the form of automated homes, smart appliances and wearable devices. These ubiquitous systems not only enhance productivity but can also provide assistance giv...
详细信息
The analysis of transportation data is considered as an essential application for Machine Learning (ML) based-intelligent transportation design and control especially for safety and improving energy management. There ...
The analysis of transportation data is considered as an essential application for Machine Learning (ML) based-intelligent transportation design and control especially for safety and improving energy management. There is a requirement to identify efficient methods for optimizing transportation operations and enhance traffic management. This study adopts exploratory data analysis to analyse transportation data including year, month, vehicle type, time period, area type, functional classification. Predictive analytics is used to predict vehicle speed as dependent variable. The study adopts four supervised ML models such as Multiple Linear Regression (MLR), Random Forest Regression (RFR), Decision Tree (DT) and Artificial Neural Network (ANN) approach for analysing the speed prediction factors. Speed prediction assists as a foundation of advanced traffic management systems. The results from the findings suggest that ANN and RFR are the commendable model for performance analytics.
Model-reference adaptive systems refer to a consortium of techniques that guide plants to track desired reference trajectories. Approaches based on theories like Lyapunov, sliding surfaces, and backstepping are typica...
详细信息
AI technology has been used in many clinical research fields, but most AI technologies are difficult to land in real-world clinical settings. In most current clinical AI research settings, the diagnosis task is to ide...
详细信息
This letter presents a gap-waveguide phase shifter based on ridged unit cells with glide-symmetric configuration. The proposed unit cell design provides a higher stable phase shift compared to a conventional ridged un...
详细信息
With the increasing demand for indoor navigation applications, indoor navigation has become a research hotspot in many technical fields. High-precision sensors are expensive, and they are often used in industrial and ...
详细信息
暂无评论