IoT-based smart garbage system for efficient food waste management.
Ontology highlight
ABSTRACT:
SUBMITTER: Hong I
PROVIDER: S-EPMC4166430 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Health care is one of the least funded sectors in Bangladesh and many other similar developing countries. People living in rural and remote areas do not have access to proper health care, and when they do, it is too expensive. This research aimed to develop a real-time health monitoring system that is cheap, easy to use, and accessible by doctors and patients. The system consists of several Internet of Things (IoT)-based sensors connected to an Arduino microprocessor, which thus measures the vital body signs of the patients. The measured readings are then transmitted to an Android application on a smartphone via a Bluetooth module. The sensors are connected to analog inputs. These sensors measure analog data, which is amplified by the microprocessor after being sorted. Doctors can also carry out the diagnosis of ailments using the data collected remotely from the patient. An Android-based mobile application that interfaces with a web-based application is implemented for efficient patients-doctors dual real-time communication. The Android application, which is connected to a MySQL database, updates the said database, which updates and displays the readings on a website accessible by both doctors and patients. Initially, the health monitor was tested using an Arduino Integrated Development Environment (IDE) monitor and a single user. Once initial simulations were successful, the proposed system was tested on five different real-human test subjects. The testing of the wireless health monitor produced successful results that measured patient vitals with a high level of accuracy. The proposed IoT-based system monitors vital signs such as the patient's body temperature, heart rate, ECG, SpO2 levels, blood pressure, and glucose levels. This system also includes a medical treatment plan by the doctors. The proposed system is novel as it integrates the IoT-based patient monitoring system with telemedicine. This proposed system has different sensors for real-time measuring the vital signs of the human body. A mobile and web application have also been integrated with this system for real-time remote patient monitoring and treatment plan. There are now systems available that only offer a telemedicine facility, where patients and doctors can have discussions, but do not have an IoT-based patient vital sign monitoring system integrated with telemedicine. The proposed system in this paper has the facility of IoT-based patient vital signs monitoring integrated with telemedicine, which makes this research work novel. The proposed system will increase the life expectancy of people throughout the world.
| S-EPMC9010939 | biostudies-literature
Project description:Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts’ inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers’ relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that‘Top Management Support (TMS)’ is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index.
| S-EPMC7500993 | biostudies-literature
Project description:The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings' energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building's data (e.g., energy management systems), energy production, energy prices, weather data and end-users' behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information.
| S-EPMC5856031 | biostudies-literature
Project description:Over the past several years, many healthcare applications have been developed to enhancethe healthcare industry. Recent advancements in information technology and blockchain technologyhave revolutionized electronic healthcare research and industry. The innovation of miniaturizedhealthcare sensors for monitoring patient vital signs has improved and secured the human healthcaresystem. The increase in portable health devices has enhanced the quality of health-monitoringstatus both at an activity/fitness level for self-health tracking and at a medical level, providing moredata to clinicians with potential for earlier diagnosis and guidance of treatment. When sharingpersonal medical information, data security and comfort are essential requirements for interactionwith and collection of electronic medical records. However, it is hard for current systems to meetthese requirements because they have inconsistent security policies and access control structures.The new solutions should be directed towards improving data access, and should be managed bythe government in terms of privacy and security requirements to ensure the reliability of data formedical purposes. Blockchain paves the way for a revolution in the traditional pharmaceuticalindustry and benefits from unique features such as privacy and transparency of data. In this paper,we propose a novel platform for monitoring patient vital signs using smart contracts based onblockchain. The proposed system is designed and developed using hyperledger fabric, which isan enterprise-distributed ledger framework for developing blockchain-based applications. Thisapproach provides several benefits to the patients, such as an extensive, immutable history log, andglobal access to medical information from anywhere at any time. The Libelium e-Health toolkitis used to acquire physiological data. The performance of the designed and developed system isevaluated in terms of transaction per second, transaction latency, and resource utilization usinga standard benchmark tool known as Hyperledger Caliper. It is found that the proposed systemoutperforms the traditional health care system for monitoring patient data.
| S-EPMC7218894 | biostudies-literature
Project description:Internet of things (IoT) applications in smart agricultural systems vary from monitoring climate conditions, automating irrigation systems, greenhouse automation, crop monitoring and management, and crop prediction, up to end-to-end autonomous farm management systems. One of the main challenges to the advancement of IoT systems for the agricultural domain is the lack of training data under operational environmental conditions. Most of the current designs are based on simulations and artificially generated data. Therefore, the essential first step is studying and understanding the finely tuned and highly sensitive mechanism plants have developed to sense, respond, and adapt to changes in their environment, and their behavior under field and controlled systems. Therefore, this study was designed to achieve two specific objectives; to develop low-cost IoT components from basic building blocks, and to study the performance of the developed systems, and generate real-time experimental data, with and without plants. Low-cost IoT devices developed locally were used to convert existing basic polytunnels to semi-controlled and monitoring-only polytunnels. Their performances were analyzed and compared with each other based on several matrices while maintaining the planted tomato variety and agronomic practices similar. The developed system performed as expected suggesting the possibility of commercial applications and research purposes.
| S-EPMC10212138 | biostudies-literature
Project description:Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.
| S-EPMC5539611 | biostudies-other
Project description:Earth's plastic pollution has increased due to the COVID-19 pandemic, and the world is on the doorstep of an enormous waste pandemic. The extensive use of mandatory personal protectives like masks, gloves, and PPE kits and the lack of proper waste management systems lead to a rise in the plastic pollution content of the earth. Such disposable and non-biodegradable personal protectives are thrown out to the environment after use. These distributed wastes pollute land, soil, and water bodies and effects their ecosystems. This research work establishes the concept of a waste-to-energy conversion approach to reuse COVID-19 scraps for green and sustainable development. Three-layered surgical masks and nitrile gloves were reused in this work after sterilization for energy harvesting and sensing applications by fabricating a 3D-printed contact-separation-based triboelectric nanogenerator. A piece of three-layered mask and nitrile gloves were placed inside the 3D structure as the top negative and bottom positive triboelectric materials with copper and aluminum as corresponding electrodes (MG-CS TENG). It can convert external mechanical motions into electrical energy. The maximum voltage, current, and power density obtained from the device are 50.7 V, 4.8 µA, and 6.39 µW/cm2, respectively, for a mechanical force of 9 N. The harvested energy was sufficient to power small-scale electronic devices like digital tally counters, wristwatches, lumex displays, and series connected 25 LEDs. MG-CS TENG was also performed as a pedal-operated touch sensor to dispense hand sanitizer. MG-CS TENG was pedal pressed to trigger a microcontroller and control the solenoid valve's opening and closing to regulate sanitizer flow. The setup was integrated using the internet of things (IoT) and Blynk cloud services for the remote monitoring and controlling of the sanitizer dispenser using a smartphone. This work contributes a substantial role in disaster management to suppress microplastic environmental pollution by reusing pandemic wastes for energy harvesting and sensing applications and preventing the spread of coronavirus through proper hand sanitization.
| S-EPMC9822840 | biostudies-literature
Project description:The agricultural sector is still lagging behind from all other sectors in terms of using the newest technologies. For production, the latest machines are being introduced and adopted. However, pre-harvest and post-harvest processing are still done by following traditional methodologies while tracing, storing, and publishing agricultural data. As a result, farmers are not getting deserved payment, consumers are not getting enough information before buying their product, and intermediate person/processors are increasing retail prices. Using blockchain, smart contracts, and IoT devices, we can fully automate the process while establishing absolute trust among all these parties. In this research, we explored the different aspects of using blockchain and smart contracts with the integration of IoT devices in pre-harvesting and post-harvesting segments of agriculture. We proposed a system that uses blockchain as the backbone while IoT devices collect data from the field level, and smart contracts regulate the interaction among all these contributing parties. The system implementation has been shown in diagrams and with proper explanations. Gas costs of every operation have also been attached for a better understanding of the costs. We also analyzed the system in terms of challenges and advantages. The overall impact of this research was to show the immutable, available, transparent, and robustly secure characteristics of blockchain in the field of agriculture while also emphasizing the vigorous mechanism that the collaboration of blockchain, smart contract, and IoT presents.
| S-EPMC8022535 | biostudies-literature
Project description:In this paper, we describe a server/client literature management system specialized for the life science domain, the TogoDoc system (Togo, pronounced Toe-Go, is a romanization of a Japanese word for integration). The server and the client program cooperate closely over the Internet to provide life scientists with an effective literature recommendation service and efficient literature management. The content-based and personalized literature recommendation helps researchers to isolate interesting papers from the "tsunami" of literature, in which, on average, more than one biomedical paper is added to MEDLINE every minute. Because researchers these days need to cover updates of much wider topics to generate hypotheses using massive datasets obtained from public databases or omics experiments, the importance of having an effective literature recommendation service is rising. The automatic recommendation is based on the content of personal literature libraries of electronic PDF papers. The client program automatically analyzes these files, which are sometimes deeply buried in storage disks of researchers' personal computers. Just saving PDF papers to the designated folders makes the client program automatically analyze and retrieve metadata, rename file names, synchronize the data to the server, and receive the recommendation lists of newly published papers, thus accomplishing effortless literature management. In addition, the tag suggestion and associative search functions are provided for easy classification of and access to past papers (researchers who read many papers sometimes only vaguely remember or completely forget what they read in the past). The TogoDoc system is available for both Windows and Mac OS X and is free. The TogoDoc Client software is available at http://tdc.cb.k.u-tokyo.ac.jp/, and the TogoDoc server is available at https://docman.dbcls.jp/pubmed_recom.
| S-EPMC3001491 | biostudies-literature
Project description:In the year 2020, the word “pandemic” has become quite popular. A pandemic is a disease that spreads over a wide geographical region. The massive outbreak of coronavirus popularly known as COVID-19 has halted normal life worldwide. On 11th March 2020, the World Health Organization (WHO) quoted the COVID-19 outbreak as a “Pandemic”. The outbreak pattern differs widely across the globe based on the findings discovered so far; however, fever is a common and easily detectable symptom of COVID-19 and the new COVID strain. After the virus outbreak, thermal scanning is done using infrared thermometers in most public places to detect infected persons. It is time-consuming to track the body temperature of each person. Besides, close contact with infected persons can spread the virus from the infected persons to the individual performing the screening or vice-versa. In this research, we propose a device architecture capable of automatically detecting the coronavirus or new COVID strain from thermal images; the proposed architecture comprises a smart mask equipped with a thermal imaging system, which reduces human interactions. The thermal camera technology is integrated with the smart mask powered by the Internet of Things (IoT) to proactively monitor the screening procedure and obtain data based on real-time findings. Besides, the proposed system is fitted with facial recognition technology; therefore, it can also display personal information. It will automatically measure the temperature of each person who came into close contact with the infected humans or humans in public spaces, such as markets or offices. The new design is very useful in healthcare and could offer a solution to preventing the growth of the coronavirus. The presented work hasa key focus on the integration of advanced algorithms for the predictive analytics of parameters required for in-depth evaluations. The proposed work and the results are pretty effectual and performance cognizant for predictive analytics. The manuscript and associated research work integrate the IoT and Internet of Everything (IoE) based analytics with sensor technologies with real-time data so that the overall predictions will be more accurate and integrated with the health sector. Supplementary Information The online version contains supplementary material available at 10.1007/s12652-022-04395-7.
| S-EPMC9466323 | biostudies-literature