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.
Depending on the application, different types of cameras are used for surveillance. Visual cameras are used for capturing images during daylight, while a thermal camera may be used for night vision, seeing through smoke or fog, vegetation monitoring, fire and heat detection using infrared patterns, etc. Data may be streamed directly from the UAV via a secure communications channel to a remote central location.
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.
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.
Mobile-enabled IoT sensors, Bluetooth beacons, infrared counters or sensors embedded in the pavement, turnstiles
RFID Readers: E.g., Handheld Typical uses: Warehouses: Tracking assets that are packaged or inside a container Hospitals: Tracking asset locations automatically within a limited distance range
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.
Sensors that monitor a building’s air quality (i.e. carbon monoxide and other volatile carbon emission detection)
Types of sensors: Remote metering, Cathodic protection, Gas density, Pipeline pressure, Custody transfer flow meters, Fire / Gas / H2S alarms, Tank levels, Tank batteries, Temperature sensors, Control valves, Flow monitoring, Electricity consumption, Structural health & deformation, Air pollution
UAV generally carries a video camera and other sensors such as laser scanner, GNSS, gyroscope,accelerometer, and barometer. Streaming the video and other sensor data to a remote location for instant storage, verification and analysis allows the survey team to gauge whether additional data needs to be collected.
Underground mining has significant safety hazards due to high-stress concentrations, weak rock masses, and limited access and air quality. Different sensors are used in mine-related activities, such as geophones in exploration and blast control, piezometers in dewatering and toxic gas detectors in working frontlines.
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.
