Remote Environmental Monitoring Research Articles

Charge generation by passive plant leaf motion at low wind speeds: design and collective behavior of plant-hybrid energy harvesters

Energy harvesting techniques can exploit even subtle passive motion like that of plant leaves in wind as a consequence of contact electrification of the leaf surface. The effect is strongly enhanced by artificial materials installed as ‘artificial leaves’ on the natural leaves creating a recurring mechanical contact and separation. However, this requires a controlled mechanical interaction between the biological and the artificial component during the complex wind motion. Here, we build and test four artificial leaf designs with varying flexibility and degrees of freedom across the blade operating on Nerium oleander plants. We evaluate the apparent contact area (up to 10 cm2 per leaf), the leaves’ motion, together with the generated voltage, current and charge in low wind speeds of up to 3.3 m s−1 and less. Single artificial leaves produced over 75 V and 1 µA current peaks. Softer artificial leaves increase the contact area accessible for energy conversion, but a balance between softer and stiffer elements in the artificial blade is optimal to increase the frequency of contact-separation motion (here up to 10 Hz) for energy conversion also below 3.3 m s−1. Moreover, we tested how multiple leaves operating collectively during continuous wind energy harvesting over several days achieve a root mean square power of ∼6 µW and are capable to transfer ∼80 µC every 30–40 min to power a wireless temperature and humidity sensor autonomously and recurrently. The results experimentally reveal design strategies for energy harvesters providing autonomous micro power sources in plant ecosystems for example for sensing in precision agriculture and remote environmental monitoring.

A Portable Agriculture Environmental Sensor with a Photovoltaic Power Supply and Dynamic Active Sleep Scheme

A portable environmental sensor for agricultural applications is proposed that addresses key challenges in power supply, data transmission, and monitoring efficiency. The sensor features a photovoltaic power supply and a PID-based dynamic active–sleep scheme for sustainable energy management, maintaining optimal battery levels under varying solar conditions. Its compact, waterproof, and dustproof design (90 mm × 90 mm × 150 mm, 844 g) ensures robust and reliable operation in diverse agricultural environments. High-precision digital sensors monitor temperature, humidity, light intensity, and CO2 concentration. Equipped with low-power NB-IoT technology, the sensor supports real-time remote environmental monitoring. Our experimental results show effective continuous operation, accurate environmental measurements, and performance comparable to established data loggers. The advanced power management and precise sensing capabilities make this sensor a competitive solution for improving smart agriculture practices, particularly in resource-limited or off-grid settings.

Environmental Monitoring System using Wireless Multi-Node Sensors based Communication System on Volcano Observations Drones

Indonesia is on the Ring of Fire and has the world's most active volcanoes. Volcanic activity has a significant effect on the landscape and on the people who live there. The difficulty of evacuating and helping victims requires hard work and sometimes even the safety of the rescue team itself. For this reason, high-tech tools are needed. Unmanned aerial vehicles (UAVs), also called drones, have become a hopeful tool for remote environmental monitoring in recent years. The system design has a monitoring platform, gateway, and sensor nodes attached to the UAV, which monitors the content of toxic gas contamination in the air. Using IoT technology, sensor data is sent wirelessly to a central monitoring station for a thorough and accurate volcanic activity study. This system is a flexible and complete way to monitor volcanic activity, learn more about it, and make it easier to respond to disasters. Tests are also done to measure system speed, including latency, and determine network service quality. The results show that data is successfully sent in real-time from the sensor nodes to the monitoring system. The average Round-Trip time for the payload transmission is 446.046226 ms. This shows how well the system works to send data from the sensors connected to the UAV to the monitoring station. The UAV has sensor nodes and a monitoring system platform. These can be used to build and optimize disaster mitigation systems.

Enhancing Microbial Fuel Cell Performance Prediction and IoT Integration Using Machine Learning and Renewable Energy

This study aims to enhance Microbial Fuel Cells (MFCs) reliability for remote environmental monitoring, emphasizing unexplored facets of accurate energy prediction and the integration of renewable energy-powered Internet of Things (IoT) devices. Following comprehensive research, design, and component procurement, an innovative and cost-effective IoT system was developed, leveraging renewable energy from MFCs. Using an Arduino UNO-WiFi, data was collected and showcased on a web page while logged in a Google Firebase database, with an Android app created for intuitive smartphone visualization. Over four months, sensor data was accumulated. An Artificial Intelligence (AI) model, employing Autoregressive Integrated Moving Average (ARIMA), precisely forecasted MFC energy production (RMSE: 0.0119 and 0.0113 for trials 1 and 2). Despite the initial energy production surge, a subsequent decline occurred due to organic matter depletion. This prototype represents an affordable and sustainable solution for cloud-based IoT environmental monitoring with AI-driven energy forecasts, embodying innovation in renewable energy applications and sustainable practices.

Application of User Interface and User Experience for Smart Greenhouse Mobile Application Design

Smart greenhouses enable remote control and monitoring of the planting environment through a mobile application. However, existing mobile applications designed for smart greenhouses often suffer from unattractive user interfaces and limited features, reducing their effectiveness in monitoring and controlling greenhouse conditions. This study’s primary objective is to design a prototype mobile application for smart greenhouses by incorporating user interface and user experience (UI/UX) principles. The performance of the designed system is evaluated through the System Usability Scale (SUS) assessment. The study follows the design thinking principles, including empathizing, defining, ideating, prototyping, and testing, to identify user problems, generate innovative ideas, and create a design prototype that aligns with user needs. The design prototype is developed using the Figma application. Results from performance testing involving 10 prospective application users indicate an outstanding usability score of 82.75, categorizing it as excellent. This outcome demonstrates the successful development of a smart greenhouse application prototype that, through thoughtful UI/UX design, offers an attractive interface and features that effectively address user requirements.

Smart Home Automated Control System using Android Application Based on Arduino

Smart Home System (SHS) is a dwelling incorporating a communications network that connects the electrical appliances and services allowing them to be remotely controlled, monitored or accessed. SHS includes different approaches to achieve multiple objectives range from enhancing comfort in daily life to enabling a more independent life for elderly and handicapped people. In this paper, the main four fields for SHS which are, home automation and remote monitoring, environmental monitoring, including humidity, temperature, fault tracking and management and finally the health monitoring has been considered. The system design is based on the Microcontroller MIKRO C software; multiple passive and active sensors and also a wireless internet services which is used in different monitoring and control processes. This paper presents the hardware implementation of a multiple- form control system for house automation and combines both hardware and software technologies. The system results show that it can be classified as a comfortable, secure, private, economic and safe system in addition to its great flexibility and reliability.

Design and Implementation of Environmental Monitoring System for Substation Based on Internet of Things

At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.

High‐Efficiency Single‐Droplet Energy Harvester for Self‐Sustainable Environmental Intelligent Networks

AbstractOur community is still far away from achieving self‐sustainable ambient intelligence, since it calls for rational energy layouts to satisfy the ubiquitous power demands from diverse terminal products. Harnessing energy directly from the surroundings thus provides ideal solutions. The majority of existing environmental harvesters rely on sophisticated procedures and expensive or toxic materials; while others attempt to streamline the complexity at the cost of compromising performance. This entails transducers that exhibit superb outputs and also employ cost‐effective, even recycled materials and straightforward protocols to render ubiquitous deployments. Here, a high‐efficiency droplet energy nanogenerator (DENG) is devised to satisfy all the requirements. The DENG is fabricated by directly coating a composite layer on a recycled digital video disk surface. It achieves superb electricity generation from one droplet, with an output voltage of >190 V at an instantaneous power density of 65 W m−2, and an energy conversion efficiency of 3.60%. Diverse demonstrations confirm the applicability of the DENG in environmental networks, encompassing self‐sustainable “on plants” sensing systems, smart building windows, and remote environmental monitoring platforms. In light of these superiorities, it is believed that the DENG may open up new alternative routes for future energy strategies.

Electrochemical Methods in the Cloud: FreiStat, an IoT-Enabled Embedded Potentiostat.

Embedded potentiostats enable electrochemical measurements in the Internet-of-Things (IoT) or other decentralized applications, such as remote environmental monitoring, electrochemical energy systems, and biomedical point-of-care applications. We report on Freiburg's Potentiostat (FreiStat) based on the AD5941 potentiostat circuit from Analog Devices, together with custom firmware, as the key to precise and advanced electrochemical methods. We demonstrated its analytical performance by various cyclic voltammetry measurements, advanced techniques such as differential pulse voltammetry, and a lactate biosensor measurement with currents in the nA range and a resolution of 54 pA. The FreiStat yielded analytical results comparable to benchtop devices and outperformed current commercial embedded potentiostats at significantly lower cost, smaller size, and lower power consumption. Decentralized corrosion analysis by a Tafel plot using the IBM Cloud showed its applicability in a typical IoT scenario. The developed open-source software framework facilitates the integration of electrochemical instrumentation into applications utilizing machine learning and other artificial intelligence. Together with the affordable and highly capable embedded potentiostat, our approach can leverage analytical chemistry toward increasingly important, more widespread and decentralized applications.

Application of UAV for Village Mapping in Pangambatan, Sumatra Utara

Pangambatan Village, as part of the Lake Toba National Strategic Area and a tourist destination, still lacks facilities, infrastructure, and professional human resources to manage its cultural and tourism potential. An initial mapping of the conditions and potential of the area is needed to drive tourism in Pangambatan Village towards sustainable tourism. This can be done by mapping environmental conditions and tourism potential in Pangambatan Village, providing recommendations for sustainable tourism management, and providing environmental management facilities. The study was carried out using Unmanned Aerial Vehicle (UAV) technology. UAV technology offers new opportunities for fast and efficient remote environmental monitoring and the collection of high spatial and temporal resolution data. The benefits of this mapping can be used to see environmental conditions and environmental pollution that may occur because of tourist activities. In addition, the use of this technology is expected to help related parties in making decisions and planning.

A Novel LoRa-Based Platform for Remote Monitoring of Large-Scale Rice Fields

The utilization of wireless sensor networks is widespread across numerous industries, including smart agriculture, where the need to remotely monitor agricultural production environments on a large scale is imperative for improving farm product quality and preserving the ecosystem. In this paper, a novel and efficient wireless sensor network framework is presented, which employs LoRa technology to facilitate remote environmental monitoring during agricultural cultivation. Our proposed network framework possesses the capability of long-range data transmission, secure data transfer from source nodes to gateway, high reliability, and easy deployment for large-scale farm monitoring applications. The effectiveness of our model was evaluated in An Giang province, Vietnam, with monitoring indicators encompassing temperature, air humidity, soil moisture, pH of water, CH4, and NH3. The findings reveal that the wireless sensor network model for remote monitoring of the rice cultivation environment fulfills the requirements of good and complete data transmission, high data network security, and a long signal transmission distance of up to 3.5 km at a reasonable cost.

Remote Online Environmental Monitoring System Based on Cloud Database

Remote Online Environmental Monitoring System Based on Cloud Database

Multilayered Helical Spherical Triboelectric Nanogenerator with Charge Shuttling for Water Wave Energy Harvesting.

As an important part of natural resources, islands support the marine economy and build a blue barrier for marine ecological civilization. However, the power supply on these islands is difficult, limiting the development of marine internet of things (IoTs). In order to break the status quo, this work applies triboelectric nanogenerators (TENGs) to island power supply and ecological monitoring. A spherical TENG with two multilayered helical units is designed to harvest water wave energy, in which the space utilization rate reaches 92.5%. Then a charge shuttling mechanism is developed to improve the electrical output. The output current and power of a single TENG without power management reach 200.3µA and 16.2mW respectively, corresponding to a peak power density of 23.2W m-3 . Moreover, a scheme of the power managed TENG is proposed for realizing large-scale wave energy harvesting. The TENG is demonstrated to successfully power a water quality detector, a Bluetooth thermo-hygrometer, and an intelligent wireless alarm system for remote environmental monitoring. This work not only proposes a new type of TENG for water wave energy harvesting with improved performance, but also provides a new strategy for intelligent ocean IoTs, which even contributes to the carbon neutralization.

Triboelectric Nanosensor Integrated with Robotic Platform for Self-Powered Detection of Chemical Analytes

Rapid on-site detection of hazardous chemicals is imperative for remote security and environmental monitoring applications. However, the implementation of current sensing technologies in real environments is limited due to an external high-power requirement, poor selectivity and sensitivity. Recent progress in triboelectric nanosensors and nanogenerators presents tremendous opportunities to address these issues. Here, we report an innovative self-powered triboelectric nanosensor for detection of Hg2+ ions, a harmful chemical pollutant, in a rapid single step on-site detection mechanism. Based on the mechanism of solid-liquid contact electrification, tellurium nanowire (Te NW) arrays serving as a solid triboelectric material as well as the sensing probe underwent periodic contact and separation with the Hg2+ solution, leading to the in situ formation of mercury telluride nanowire (HgTe NWs) owing to the selective binding affinity of Te NWs toward Hg2+ ions. To realize the on-site sensing potential, Te NW arrays were mounted onto the robotic hands equipped with additional wireless transmission functionality for rapid detection of Hg2+ ions in resource-limited settings by employing a simple "touch and sense" mechanism. Such a demonstration of direct integration of self-powered sensors with robotics would lead to the development of low-cost, automated chemical sensing machinery for the on-field detection of harmful analytes.

Microservice architecture for a remote management platform for pastured poultry farming using Amazon Web Services and wireless mesh sensor networks

Introduction: A variety of innovative solutions known as Precision Livestock Farming (PLF) technologies have been developed for the management of animal production industries, including Wireless Sensor Networks (WSN) for poultry farming.
 Problem: Current WSN-based systems for poultry farming lack the design of robust but flexible software architectures that ensure the integrity and proper delivery of data.
 Objective: Designing a microservice-based software architecture (MSA) for a multiplatform remote environmental management system based on Wireless Mesh Sensor Networks (WMSN) to be deployed in pastured poultry farming spaces.
 Methodology: A review about MSAs designed for animal farming was conducted, to synthesize key factors considered for the design process of the system data flow, microservice definition and the environmental monitoring system technology selection.
 Results: A cloud MSA with a multi layered scheme using the Amazon Web Services (AWS) platform was developed, validating the persistence of environmental data transmitted from WMSN prototype nodes to be deployed in mobile chicken coops.
 Conclusion: Defining an End-to-End data flow facilitates the organization of tasks by domains, allowing efficient event communication between components and network reliability both at the hardware and software levels.
 Originality: This study presents a novel design for a remote environmental monitoring system based on WMSN for mobile coops used in pastured poultry and a multi layered MSA cloud management platform for this specific type of food production industry.
 Limitations: Software architecture technology selection was based only on services offered, to the date of the study, in the free tier of the Amazon Web Service platform.

Health-Related Telemonitoring Parameters/Signals of Older Adults: An Umbrella Review.

Aging is one of the greatest challenges in modern society. The development of wearable solutions for telemonitoring biological signals has been viewed as a strategy to enhance older adults' healthcare sustainability. This study aims to review the biological signals remotely monitored by technologies in older adults. PubMed, the Cochrane Database of Systematic Reviews, the Web of Science, and the Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports were systematically searched in December 2021. Only systematic reviews and meta-analyses of remote health-related biological and environmental monitoring signals in older adults were considered, with publication dates between 2016 and 2022, written in English, Portuguese, or Spanish. Studies referring to conference proceedings or articles with abstract access only were excluded. The data were extracted independently by two reviewers, using a predefined table form, consulting a third reviewer in case of doubts or concerns. Eighteen studies were included, fourteen systematic reviews and four meta-analyses. Nine of the reviews included older adults from the community, whereas the others also included institutionalized participants. Heart and respiratory rate, physical activity, electrocardiography, body temperature, blood pressure, glucose, and heart rate were the most frequently measured biological variables, with physical activity and heart rate foremost. These were obtained through wearables, with the waist, wrist, and ankle being the most mentioned body regions for the device's placement. Six of the reviews presented the psychometric properties of the systems, most of which were valid and accurate. In relation to environmental signals, only two articles presented data on this topic. Luminosity, temperature, and movement were the most mentioned variables. The need for large-scale long-term health-related telemonitoring implementation of studies with larger sample sizes was pointed out by several reviews in order to define the feasibility levels of wearable devices.

Internet of Things (IoT)-Based Environmental Monitoring and Control System for Home-Based Mushroom Cultivation

The control and monitoring of the environmental conditions in mushroom cultivation has been a challenge in the mushroom industry. Currently, research has been conducted to implement successful remote environmental monitoring, or, in some cases, remote environmental control, yet there is not yet a combination of both these systems providing live stream images or video. As a result, this research aimed to design and develop an Internet of things (IoT)-based environmental control and monitoring system for mushroom cultivation, whereby the growth conditions of the mushrooms, such as temperature, humidity, light intensity, and soil moisture level, are remotely monitored and controlled through a mobile and web application. Users would be able to visualize the growth of the mushroom remotely by video and images through the Internet. The respective sensors are implemented into the mushroom cultivation process and connected to the NodeMCU microcontroller, which collects and transfers the data to the cloud server, enabling remote access at any time through the end device with internet connection. The control algorithm regulates the equipment within the cultivational chamber autonomously, based on feedback from the sensors, in order to retain the optimum environment for the cultivation of mushrooms. The sensors were tested and compared with manual readings to ensure their accuracy. The implementation of IoT toward mushroom cultivation would greatly contribute to the advancement of the current mushroom industry which still applies the traditional cultivation approach.

Data Acquisition and Remote Monitoring of Geological parameters for Landslide Prediction using WSN

Aiming at the problems of a large amount of redundant information, low data accuracy and difficulty in system monitoring when wireless sensor network nodes collect data. An efficient technique of data collection and remote monitoring system based on wireless sensor network is proposed. The system uses WSN nodes to real-time collection of external environment parameters. A software design for Wireless Sensor Network formation, data fusion, data transmission and transferring data to the host computer, and use of WIFI/GSM as a means of transmission to build a remote monitoring platform. The test results show that the system can realize remote real-time monitoring of the external environment, geophysical parameters and the use of data fusion algorithms increases the transmission rate and data accuracy between nodes.

A Sensor Array-based Control System Design for the Interior Environment of Driverless Cars

Highly intelligent driverless cars require intelligent, user-friendly and high-safety interior environment control systems to match. In this paper, through the use of vision sensors, sound sensors and a variety of environmental sensors to form a sensor array, and through the embedded microprocessor for centralized control, the design completed with face recognition door opening, cry detection window opening, vibration detection alarm, haze detection defrost, automatic thermostat control, automatic light brightness control, internal environment remote monitoring and other functions in one of the driverless car intelligent internal environment control system. The test results show that the system designed in this paper is a good solution to the problem. The test results show that the system designed in this paper is functionally rich and scalable, highly intelligent and suitable for the needs of the general public, and helps to improve the ride comfort and safety of driverless cars.

Non-line-of-sight outdoor channel identifcation for wireless sensor networks based on impluse radio ultra wide band

Wireless sensor networks (WSN) have become increasingly popular in a variety of fields in recent years. This is due to the development of their capabilities, which include remote environmental monitoring, process automation, telemedicine, and many other domains. Besides, among the widely used modern WSN radio technologies, we find impluse radio ultra wide band (IR-UWB) that is recognized by their advantages regarding low power consumption, low cost, low complexity and high resistance to multipath fading in outdoor wireless networks. Energy consumption minimization, packet delivery ratio improvement and latency minimization are the main objectives in this work. The chosen performance metrics (energy consumption, packet delivery ratio and latency) are justified by the direct impact of these three parameters on the network’s efficiency. Accordingly, we proposed and introduced an outdoor non-line-of-sight (NLOS) packet delivery ratio using broadband radio access network (BRAN) channel to improve WSN’s based on IR-UWB performance in terms of energy consumption, packets delivery ratio (PDR) and latency.