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– Global positioning system tag – communicates with GPS satellites to establish position with high accuracy, but only when the tag or animal is on land or at the water surface – Fastloc Global positioning system tag – GPS tag for aquatic animals that surface or haul out, when the tag locks onto the GPS satellite network to establish position with high accuracy – Pop-up satellite archival tag – after some period of time recording sensor data, the tag detaches itself from the animal and floats to the surface where it uses satellite connectivity to uplink the data stored on the tag – Acoustic tag – attached to the animals being tracked emit acoustic signals (typically ultrasound) which travel through water much better than RF signals. These signals are then received by buoys, which can then use satellite communications to backhaul the data to where it’s needed.

Camera types used on agrobots: – RGB cameras – extensively used in agricultural machine vision applications for fruit/plant detection, yield prediction, segmentation tasks, disease detection, ripeness detection, weed detection and insects detection – Hyperspectral, thermal, or ultrasonic cameras – typically provide better results than conventional RGB color images – Stereoscopic cameras – provides 3D plant structure information (dimension of crops (depth information, crop height, leaf shape, leaf area etc.)) Critical factor is the camera’s resolution, which should be high enough to capture the details of the scene especially in the cases of insect and disease detection.

Driverless vehicles and Autonomous Drilling Systems that can operate without human intervention allow operations around the clock, enabling minerals to be extracted and processed in shorter time-frames. Real-Time Kinematic GPS (RTK-GPS) is used In underground mines due to a limited range of signal transmission below the surface and lack of satellite coverage in depth. RTK-GPS is used to ensure autonomous vehicles and drilling systems have clear path-tracking and collision avoidance capabilities. GPS-guided drilling operations. GPS provides accurate information to the drill head to control its direction deep within the earth.

Monitoring emissions from factories in real-time involves a variety of sensors and instruments designed to measure different types of pollutants. These sensors are often networked together and connected to a central monitoring system that collects, analyzes, and reports data in real time. This enables factory operators and regulatory agencies to track emissions continuously and ensure compliance with environmental regulations, as well as to make informed decisions about emission control and reduction strategies. Gas Analyzers: These sensors are used to detect and quantify specific gases in the air, such as carbon dioxide (CO2), sulfur dioxide (SO2), nitrogen oxides (NOx), and volatile organic compounds (VOCs). Particulate Matter (PM) Sensors: These sensors measure the concentration of particulate matter in the air. Opacity Monitors: These are used to measure the opacity of emissions from smokestacks, which is an indicator of particulate matter concentrations. Flame Ionization Detectors (FID): FIDs are used to measure total hydrocarbon levels in emissions. FTIR (Fourier Transform Infrared Spectroscopy) Analyzers: These analyzers can detect a wide range of gases and are particularly useful for identifying complex mixtures of pollutants. UV Spectrometers: Ultraviolet spectrometry can be used to measure specific gases like ozone (O3) and sulfur dioxide (SO2) based on their absorption characteristics in the UV range. Chemical Sensors and Biosensors: These are used to detect and measure specific chemical compounds in emissions. Temperature, Pressure, and Flow Sensors: These sensors provide additional data on the emission conditions, such as the temperature and pressure of the emitted gases and the flow rate of emissions.

Rain Gauges: Modern rain gauges often come equipped with wireless communication capabilities, allowing them to transmit data on rainfall amounts to monitoring centers in real time. Stream Gauges: Many stream gauges are designed to wirelessly transmit data on water levels and flow rates, providing crucial information for flood forecasting.Soil Moisture Sensors: These sensors can be equipped with wireless communication to send soil moisture data to a central system, which helps in assessing the risk of flooding, especially in areas prone to flash floods. Pressure Transducers: Used in various water bodies, these sensors can wirelessly transmit water pressure data, which is then used to calculate water levels. Ultrasonic Sensors: These can be set up to measure water levels and then transmit the data wirelessly to a central monitoring system. Anemometers: Modern anemometers can send wind data wirelessly to meteorological centers, contributing to broader weather pattern analysis for flood prediction. Tide Gauges: In coastal areas, tide gauges equipped with wireless communication capabilities transmit sea level data, which is crucial for predicting storm surges and coastal floods.

Some of the key types of sensors used in urban air quality monitoring include: Particulate Matter (PM) Sensors: These sensors measure concentrations of particulate matter Nitrogen Dioxide (NO2) Sensors: NO2 is a common urban pollutant, often produced by vehicle exhaust and industrial processes. Sulfur Dioxide (SO2) Sensors: Commonly produced by industrial processes, SO2 levels are often monitored using ultraviolet fluorescence or electrochemical sensors. Ozone (O3) Sensors: Ozone at ground level is a harmful pollutant, and its concentration is typically monitored using ultraviolet (UV) photometry or electrochemical cells. Carbon Monoxide (CO) Sensors: CO is a colorless, odorless gas resulting from incomplete combustion. It’s usually monitored in urban environments using electrochemical sensors. Volatile Organic Compounds (VOCs) Sensors: VOCs are emitted from a variety of sources, including vehicle exhaust, industrial processes, and consumer products. Meteorological Sensors: These sensors measure environmental conditions like temperature, humidity, wind speed, and wind direction, which are important for understanding and interpreting air quality data.