Monitoring Carbon Emission from Industrial Users by Identifying Multi-State Load in Advance Metering Infrastructure
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This dataset was curated mainly to cater to mitigation strategies for the Human-Peafowl Conflict that exists in these regions. The absence of natural predators has contributed to a significant increase in the peafowl population, exacerbating challenges for farmers. Peafowls are sometimes considered agricultural pests due to their tendency to feed on and damage crops. The vocalizations are from the Indian Peafowl (Pavo cristatus), a species native to the Indian subcontinent and especially abundant in India and Sri Lanka.
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This dataset is shared as part of the paper Towards scalable and low-cost WiFi sensing: preventing animal-vehicle collisions on rural roads, submitted to the IEEE Internet of Things Journal (IoT-J). It contains Wi-Fi Channel State Information (CSI) data from roadway crossings of small and large animals, persons and vehicles in rural environments.
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Time-series satellite images provide a sequence of spatial data captured over regular intervals, enabling the analysis of changes on the Earth's surface over time. These images are particularly useful in monitoring environmental phenomena, land use changes, urban development, and agricultural patterns. By examining the same location at different time points, time-series satellite imagery allows for the detection of trends, anomalies, and transitions in land cover.
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The scope of this challenge is development of signal processing methods for localizing a gas source using in-situ wind speed and gas concentrations measurements. The methods are designed to advance robotic olfaction and associated autonomous robotic exploration techniques -- highly relevant yet challenging problems in the context of gas source localization, environmental monitoring, and civil security, to name only a few.
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Animal habitat surveys play a critical role in preserving the biodiversity of the land. One of the effective ways to gain insights into animal habitats involves identifying animal footprints, which offers valuable information about species distribution, abundance, and behavior.
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We investigated the long term functionality of the designed PMCS in a practical use case where we monitored plant growth of classical horticulture Dianthus flowers (Dianthus carthusianorum) under the effect of plastic mulching over a period of 4 months. This use case represents a common phenological monitoring case that can be used in agricultural studies. For this, we integrated our PMCS in an embedded vision camera equipped with the openMV H7 Plus board in a waterproof housing [26]. The system shown in Fig.
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Social Media Big Dataset for Research, Analytics, Prediction, and Understanding the Global Climate Change Trends is focused on understanding the climate science, trends, and public awareness of climate change. The use of dataset for analytics of climate change trends greatly helps in researching and comprehending global climate change trends.
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The dataset aims to facilitate research in the optimization of the carbon footprint of recipes. Consisting of 30 Excel files processed through various Python scripts and Jupyter notebooks, the dataset serves as a versatile resource for both performance analysis and environmental impact assessment. The unique attribute of this dataset lies in its ability to calculate representative values of carbon footprint optimization through multiple algorithmic implementations.
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