Air pollution is a critical problem in densely populated urban areas, with traffic significantly contributing. To mitigate the adverse effects of air pollution on public health and the environment, ...there is a growing need for the real-time monitoring and detection of pollution spikes in transportation. This paper presents a novel approach to using Internet of Things (IoT) edge networks for the real-time detection of air pollution peaks in transportation, specifically designed for innovative city applications. The proposed system uses IoT sensors in buses, cabs, and private cars. These sensors are equipped with air quality monitoring capabilities, including the measurement of pollutants such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon dioxide (CO2). The sensors continuously collect air quality data and transmit them to edge devices within the transportation infrastructure. The data collected by these sensors are analyzed, and alerts are generated when pollution levels exceed predefined thresholds. By deploying this system within IoT edge networks, transportation authorities can promptly respond to pollution spikes, improving air quality, public health, and environmental sustainability. This paper details the sensor technology, data analysis methods, and the practical implementation of this innovative system, shedding light on its potential for addressing the pressing issue of transportation-related pollution. The proposed IoT edge network for real-time air pollution spike detection in transportation offers significant advantages, including low-latency data processing, scalability, and cost-effectiveness. By leveraging the power of edge computing and IoT technologies, smart cities can proactively monitor and manage air pollution, leading to healthier and more sustainable urban environments.
In the farming industry, the Internet of Things (IoT) is crucial for boosting utility. Innovative agriculture practices and medical informatics have the potential to increase crop yield while using ...the same amount of input. Individuals can benefit from the Internet of Things in various ways. The intelligent farms require the creation of an IoT-based infrastructure based on sensors, actuators, embedded systems, and a network connection. The agriculture sector will gain new advantages from machine learning and IoT data analytics in terms of improving crop output quantity and quality to fulfill rising food demand. This paper described an intelligent medical informatics farming system with predictive data analytics on sensing parameters, utilizing a supervised machine learning approach in an intelligent agricultural system. The four essential components of the proposed approach are the cloud layer, fog layer, edge layer, and sensor layer. The primary goal is to enhance production and provide organic farming by adjusting farming conditions as per plant needs that are considered in experimentation. The use of machine learning on acquired sensor data from a prototype embedded model is investigated for regulating the actuators in the system. Then, an analytics and decision-making system was built at the fog layer, employing two supervised machine learning approaches including classification and regression algorithms using a support vector machine (SVM) and artificial neural network (ANN) for effective computation over the cloud layer. The experimental results are evaluated and analyzed in MATLAB software, and it is found that the classification accuracy using SVM is much better as compared to ANN and other state of art methods.
In this paper, we present an extremely compact ultrawideband (UWB) monopole microstrip patch antenna for a wireless body area network (WBAN). The proposed antenna is fabricated on a flexible Rogers ...RT-5880 dielectric substrate of thickness 0.5 mm and has an overall size of 20×15×0.5 mm3. The proposed antenna achieves a wideband characteristic with the help of a modified ground plane with a monopole pair. The monopole antenna is fed through a microstrip line and has a good impedance matching over a frequency band of 3.2 to 15 GHz (and beyond), with an axial ratio below 3 dB and a high efficiency of 77–95%. This antenna is designed to cover almost the complete UWB range; bandwidth for antenna is 11.52 GHz (3.48-15 GHz). The antenna has a realized gain of 2.3–7.2 dBi throughout the frequency band and has been tested for conformality. Measured results are found to be in good correlation with the simulated results. The antenna has also been tested for specific absorption rate (SAR) values within the simulation to compare with Federal Communications Commission (FCC) limits and verify their suitability for the Internet of Things- (IoT-) based wearable body area network.
Air pollution spikes have been causing harm to human beings and the environment. Most exposure to Air pollution spikes has demonstrated a significant impact on mental health, especially children at ...an early age. That lead to suicide or depression. Previous research concentrated on air pollution in general. Existing monitoring systems do not consider Short-term air pollution peaks. This paper presents the co-design of the hardware and software for IoT to monitor air pollution spikes for a short duration in real-time monitoring. The system comprises two technologies like edge computing to capture short-term exposure and a mathematical model for distribution in analyzing the captured data. This system ensures the presence of the spikes start and end for each pollutant. Monte Carlo simulation has been used in this research to predict the next spike of each pollutant. Artificial Intelligent is used to analyze immutable data for a short term prediction. After the analysis, legislators based on intelligent contracts created using blockchain to reduce pollution based on its source.
Monitoring System to Strive against Fall Armyworm in Crops Case Study: Maize in Rwanda Hanyurwimfura, Damien; Nizeyimana, Eric; Ndikumana, Faustine ...
2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Conference Proceeding
The food security has received much attention due the hunger that usually affects some countries in Africa. Pests are very dangerous to crops and reduce the harvest of affected crop and can cause ...risk if no technical methods are applied to strive against them. Fall armyworm (FAW) is one the pest that has attacked the priority stable crop of Rwanda (maize) since last year 2017. This reduced the expected harvest from this crop. The presence of this pest costs the government to use drones and other special forces to strive for it, but pest will remain a problem if there is no regular, automatic way to detect the pest and strive for it at the early days of attacking the crop. This paper introduces a design of a prototype of an automated system that will be able to detect the presence of a fall armyworm in the field. The system will use the new technology of Internet of Things (IoT) where sensors are used to identify the pest location. Once the presence of the pest is detected in the farm, the system will be able to give the information of the affected crop and notify the farmer through his/her mobile phone who will immediately react accordingly. Through the authorization from the farmer, the system will be able to pump pesticides to kill both larvae and eggs of fall armyworm on the affected crop. This automated system will save the farmer's time, as it will monitor the crops while the farmer is occupied with other activities. Lastly the system will help to increase the production of maize in Rwanda since the crop will be safe from the pest.
Vehicle based logistics are hinged on their ability to timely deliver goods, services, and people. The classical expression of “time is money” comes alive in the logistics industry yielding ...potentially huge financial and health consequences in case of missing deadlines. This is especially the case for time sensitive pharmaceuticals, delivery of perishable goods, delivery of people travelling, delivery of services in fault fixing/recovery sector. All these use cases motivate the need for an immutable, secure, and immortalized process of tracking time. To solve this challenge, this paper presents prototype-based research that integrates the 4th industrial revolution technologies of vision Internet of Things (IoT), Artificial Intelligence (AI)-based Optical Character Recognition (OCR) and blockchain. The developed prototype features a Raspberry-PI board embedding a camera, an Artificial Intelligence (AI) model to recognize plate letters from the image and a crypto wallet to sign the logging of plate number and time events on the NEAR blockchain, an emerging sharded, proof-of-stake, layer-one blockchain that is simple to use, secure and scalable. The effective operation of the developed prototype has been validated inside a campus parking and shows an accuracy of 80%. The benefits of transparency, security, and immutability of the blockchain combined with the intelligence, data capture, and processing of IoT will enable to develop accountability solutions trusted by all different logistic stakeholders.
Orthogonal frequency division multiplexing (OFDM) was endorsed in recent digital communication technologies such as 4G-LTE to cope with multipath fading channel, and respond to increasingly high data ...rate demand. Despite its attractive features, OFDM based systems suffers from High Peak to Average Power Ratio (PAPR) which limits its application to a certain level. In this paper, the peak windowing technique is investigated in details and the effect of window size on PAPR reduction and BER improvement performance is the main analysis concern by taking into consideration system circuitry non-linearity characteristics. The performance of five different peak windowing functions on PAPR reduction performance was analyzed, Individual window function performance for PAPR reduction were evaluated and the window function with the optimum performance over others was selected and used to assess the effect of window size of peak windowing for PAPR reduction in LTE system with non-linear High power Amplifier (HPA). The simulation results and analysis of proposed approach shows that Hann window function of window size ws=8 provide a 2.094dB PAPR reduction from 10.207dB to 8.113dB at 10-2 probability, with BER degradation of 0.0065dB and 0.214dB at 10-1 and 10-2probabilty respectively. A Comparative performance analysis of the proposed algorithm with other allied recent proposed approaches on PAPR reduction such as Gaussian windowing was carried out; a good performance of the proposed method is observed.
Exposure to air pollution spikes cause health problems to regularly exposed organisms, raising the need to monitor them in real-time. Existing air pollution monitors mainly use a cloud-centric design ...considering relatively constant pollution, therefore duty-cycling sensors with long sleep periods to save their batteries. Such design is however inefficient for monitoring pollution spikes. Furthermore, since spikes vanish rapidly, integrity of monitoring data is very important. This paper presents a framework integrating edge-centric design and blockchain in monitoring air pollution spikes, while using short-term prediction artificial intelligence to timely alert pollution emitters about exceeding long-term average pollution limits defined by standards.
Tracking farmland loss Nizeyimana, Egide L; Peterson, Gary W; Warner, Eric D
Geotimes,
01/2002, Letnik:
47, Številka:
1
Magazine Article
Nizeyimana et al discuss the loss of farmland in the US. Since the early 1960s, public concern has increased that urbanization might be eclipsing potential farmland. The national perspective has ...focused on the loss of highly productive farmland as urban development expands into agricultural landscapes.
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