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.
Conductivity, Temperature, and Depth (CTD) Sensors: These are widely used in oceanography. CTD sensors measure conductivity (to infer salinity), temperature, and depth simultaneously, providing comprehensive data essential for climate change studies.
Digital Temperature Sensors: Placed in various parts of a rainforest, these sensors can provide detailed temperature data, helping to detect and analyze sudden temperature variations.
Fiber-optic Distributed Temperature Sensing (DTS) systems and pressure gauges enable critical monitoring during exploration and energy production for Enhanced Geothermal Systems (EGS). These sensors can be used to: – Estimate production potential in or between new wells by measuring the distributed temperature and the point pressure, or pressure measured at the bottom of the well. These measurements allow the calculation of reservoir size, flow resistance between wells (if multiple wells are instrumented), well bore damage caused by drilling, effectiveness of the fracturing operations, and well completion. – Monitor surface and subsurface scale buildup and chemical clean-up. Scale, a mineral residue precipitated from geothermal fluid in response to changes in water pressure and temperature, builds up on pipe walls and will, over time, form a thick, insulating layer that limits flow and may block a pipe. Chemicals are injected into the pipe to remove the accumulated scale. By understanding severity of the scaling, operators can better consider what mitigation options are most suitable as well as minimize the use of expensive chemicals. – Provide permanent monitoring of injector and producer wells to allow identification of the specific zones and fractures that produce fluids. – Perform integrity monitoring for casing and tubing leaks to avoid contaminating ground water and subsurface aquifers.
GPS for autonomous navigation in open-field cultivation environments Robotic data collection platform equipped with RADAR, liDAR, ultrasonic radar sensors, spectrometers, fluorometers
Infrared Thermal Imaging: Used to map urban heat islands from a distance, often from airborne platforms or satellites. Networks of Digital Temperature Sensors: Deployed across different urban areas, these sensors can provide granular temperature data, highlighting variations within a city. Weather Stations: Often used in urban settings, weather stations can provide comprehensive environmental data, including temperature, which is crucial for studying urban heat island effects.
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.
Satellites: Geostationary and polar-orbiting weather satellites are equipped with advanced sensors to monitor wind patterns at high altitudes globally. They are particularly useful for tracking large-scale weather systems and providing data for flight path planning over remote areas like oceans. Satellite sensors that track high-altitude wind speeds can range from those capturing basic wind vector data to more complex imaging systems.
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.
Wind Sensors (Anemometers): measure wind speed and direction, key factors in sandstorm formation. By understanding wind patterns, it becomes easier to predict the movement and intensity of sandstorms.
