Time Series Forecasting Using Double Exponential Smoothing for Predicting the Major Ambient Air Pollutants

Bose, Rajesh; Dey, Raktim Kumar; Roy, Sandip; Sarddar, Debabrata

doi:10.1007/978-981-13-7166-0_60

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…For observation of food crops, detector-based systems, humus, fields, domestic animals and for other important factors, detector-based systems are used and ultimately this system is used for enhancement of food production. Automobiles related to smart agronomy, drones, independent machines are connected with this agronomy based on intelligent systems for predictive analysis and planning [30][31][32].…”

Section: Usage Of Iot In Building Up Smart Agronomymentioning

confidence: 99%

Agronomy with IoT Devices: The Smart Solution for Detection of Diseases of Betel Leaves

Sarkar¹,

Karforma²,

Bhattacharya³

et al. 2023

ujar

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The growth of the entire population in the entire world and scarcity of food crops are the most challenging concept nowadays and for solving these challenges, new mechanization like artificial intelligence, Internet of Things and the mobile internet are used for solving this above-mentioned real-life problem. From 2019 onwards, a current perspective regarding Intelligent Agronomy has been focused on. For this smart system, Internet of Thing (IoT) is the column pillar because sensor devices are being connected to perform various basic tasks. Different sensors are used in the smart irrigation system which is based on smart controllers and detectors for vigilance of water line, watering efficacy and environment. Automatic leaf disease detection is also a very important concept for monitoring the growth of food crops and other plant leaves with medicinal value. This system also detects the symptoms of the disease in the plant leaves automatically. In the proposed decision-making system the authors have collected a set of betel leaf images and have utilized image content characterization and Support Vector Machine (SVM) classifier. Different stages like initialization, bifurcation, eradication of characteristics and orderly arrangement have been involved in image processing mechanisms for analyzing decisions. At the time of processing, an input image is being rescaled as per requirement. Authors of this research paper have eliminated color and surface characteristics from input image sets for classification and training. The proposed system will be able to analyze the test images automatically for making decisions about the leaf whether it is abnormal or good.

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Section: Usage Of Iot In Building Up Smart Agronomymentioning

confidence: 99%

Agronomy with IoT Devices: The Smart Solution for Detection of Diseases of Betel Leaves

Sarkar¹,

Karforma²,

Bhattacharya³

et al. 2023

ujar

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“…Holt's DES allows the model to adjust the trend and slope rate flexibly, where 𝟎 < 𝜶 < 1 and 𝟎 < 𝜷 < 1 (Bose, Dey, Roy, & Sarddar, 2019).…”

Section: Double Exponential Smoothingmentioning

confidence: 99%

Demand Forecasting of The Automobile Sales Using Least Square, Single Exponential Smoothing and Double Exponential Smoothing

Fahrudin

Ambariawan

Kamisutara

2021

ijbs

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Sales strategies require the right managerial in marketing products with the development of technology and communication, the decision making in product sales supported by complete data and can be analyzed into intelligence business solutions. The research discussed and provided solutions about how to forecast future demand targets from a set of data history by making a predictive model of product demand in the real case. The research study was obtained from automobile sales, which the company probably set the strategy from the forecast result of automobile sales by the system in the future. The research used forecasting methods such as Least Square, Single Exponential Smoothing, and Double Exponential Smoothing to achieve a small percentage of prediction error. The dataset was collected from Mitsubishi Motors Corporation which obtained 60 samples of popular product types such as Pajero, FE and L300 from 2014 to 2018 over a period of months. The experimental results reported that Double Exponential Smoothing has given a better performance than other methods. The forecasting result of Pajero reached the MAPE of 3.26%, FE reached the MAPE of 3.24%, and L300 reached the MAPE of 3.37%. This study indicates that the selection of the forecasting method depends on the actual data pattern and the adjustment of the parameters in predicting future points.

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“…From the functional diagram above you may already have an idea about how this system exactly works but here, we are going to discuss the diagram mentioned above in detail. We have used the following sensors for this project: BP Sensor (measures Human blood pressure), SpO2 Sensor (measures human blood oxygen saturation), Temperature Sensor (measures the amount of heat stored in the human body), and DHT11 Sensor (measures ambient air temperature and humidity) [36]. Among these sensors, the BP sensor, SpO2 sensor, and Body Temperature sensors are physical sensors that mean an individual has to come into contact with these sensors, and then they will work, while the DHT11 sensor works on the environment.…”

Section: Functional Diagrammentioning

confidence: 99%

“…The room Temperature and Humidity sensor collects data from the environment. The user needs to copy the IP address displayed on the digital display on our device and put it into the browser on their computer or mobile phone [36]. Figure 3 After entering the IP on your browser the real-time output can be seen on your Mobile Phone as shown in figure 4.…”

Section: Functional Diagrammentioning

confidence: 99%

IoT-based Tetra Health Surveillance System (THSS)

Roy

Ghosh

et al. 2021

int.jour.sci.res.mana.

Self Cite

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Nowadays, we are very conscious about our health because of how the covid-19 virus has changed our day-to-day life. IoT healthcare devices can be really helpful in this pandemic situation when we are all stuck in our homes. We have witnessed that IoT devices got very popular during this pandemic and the term ‘IoT’ also got really famous in the healthcare industry. If the hospital is far away from someone’s home, then using these portable monitoring devices one can keep track of their well-being. Health is the most important aspect for any individual, so in this paper, we propose a solution named the IoT-based Tetra Health Surveillance System (THSS) which helps us to monitor people who live by themselves or elderly people who want to continuously monitor their vitals due to underlying health conditions. Our proposed solution also displays the Temperature and Humidity, Blood pressure, Body Temperature, and SpO2/Blood Oxygen level at any given moment. This work will have a significant technical and commercial benefit because an individual can monitor all their vitals in one place and they don’t have to buy separate pieces of equipment to monitor each one of their vitals. This proposed device can be an all-in-one solution that is cost-effective and easy to use.

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Time Series Forecasting Using Double Exponential Smoothing for Predicting the Major Ambient Air Pollutants

Cited by 7 publications

References 9 publications

Agronomy with IoT Devices: The Smart Solution for Detection of Diseases of Betel Leaves

Agronomy with IoT Devices: The Smart Solution for Detection of Diseases of Betel Leaves

Demand Forecasting of The Automobile Sales Using Least Square, Single Exponential Smoothing and Double Exponential Smoothing

IoT-based Tetra Health Surveillance System (THSS)

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