Tag Archives: sensors

Farming With Drones & Robots

According to Heidi Johnson, crops and soil agent for Dane County, Wisconsin, “Farmers are the ultimate “innovative tinkerers”.” Farming, through the ages, has undergone vast changes. Although in developing worlds, you will still find stereotype farmers planting his seeds and praying for rain and good weather while waiting for his crops to grow, farm technology has progressed. Therefore, we now have twenty-four hour farming and driverless combines and autonomous tractors have moved out of agro-science fiction. Farmers now are good at developing things that are close to what they need.

For example, the Farm Tech Days Show has farmers discussing technology ranging from the latest sensors to cloud processing for optimizing their yield and robotics that can improve manual tasks. Most farmers are already aware of data analytics, cloud services, molecular science, robotics, drones and climate change among other technological jargon. The latest buzz in the agricultural sector is about managing farms that are not a single field, but distributed in multiple small units. This requires advanced mapping and GPS for tailoring daily activities such as the amount of water and fertilizer that each plant needs.

That naturally leads to observation, measurements and responding in real time. Because such precision farming means technological backup, with data being the crux of the issue to respond to what is actually happening in the field. A farmer would always like to know when his plants are suffering and the cause of their suffering.

For example, farmers want sensors that can tell them about the nutrient levels in the soil at a more granular level – potassium, phosphorus and nitrogen, etc. They also want to know how fast the plant is taking up such nutrients – the flow rate. This information must come in real time from sensors and there must be diagnostic tools to make sense of the data.

Although NIFA, the National Institute of Food and Agriculture were talking about the Internet of Ag Things, the concept is not new to farmers. In fact, farmers are already collecting information from both air and ground. They are doing this by flying drones, inserting moisture sensors into ground and placing crop sensors in machines when spraying and applying fertilizers.

Presently, what farmers are lacking is a cost effective, adequate broadband connection. Although Internet connectivity exists even in remote areas, thanks to satellite linkages, these are not cost effective to the farmer, as they have to deal with increasing amounts of data flow.

The current method farmers use is to collect data from the field on an SD card or thumb drive and plug it into their home computers. They transfer this data for analysis to services where crop consultants or co-operative experts are available. The entire process of turnaround takes a few days.

What farmers need is end-node farming equipment with the necessary computing power. This could help with processing and editing the raw data and sending only the relevant part direct to a cloud service. This requires an automated process and a real-time operation. With farms getting bigger, farmers need to cover much more acreage, while dealing with labor shortage and boosting yields in their farms.

Make Your Raspberry Pi Follow Walls

The versatile single board computer, the Raspberry Pi or RBPi, makes an excellent base for an autonomous bot using a rover 5 platform. The bot uses custom laser range finders for basic wall following. It features speed control of each track, regulated by PID using feedback from its quadrature encoders, giving it the ability of directional control. The basic features are explained below.

Batteries power the bot, feeding two separate switching mode regulators. One supplies power to the motors via the H-bridge, while the other powers the RBPi and other electronic devices. The H-bridge and the SMPS reside on the lower layer of the bot, while the sensors and the RBPi are on the upper layer. Mechanical standoffs separate the two layers, and the physical separation between the two layers creates a barrier for the electromagnetic fields from the power system that would otherwise affect the compass.

A Pixy CMUCam and a line laser form the laser range finding system of the bot. A simple piece of PVC pipe with slots cut into it breaks up the beam from the line laser. That allows the cam to recognize the color of the laser blobs as it reports this data via I2C to the RBPi, which then uses simple trigonometry for converting the data into vectors representing range and angles.

A sonar device mounted on the front of the bot implements a fairly simple crash prevention mechanism. The laser range finding system may also be used for a more sophisticated crash prevention system. Even though the bot is meant for autonomous operation, it also has a basic user interface built-in to allow control for testing purposes. The interface allows simple operations such as setting the heading and limiting the forward and backward speeds. It uses some feedback from the current heading of the robot.

For testing the laser range finding, the bot has a built-in GMR or graphical mapping representation, but in a minimal configuration. Using the GMR reveals a basic difference between the mapping from the sonar device and that from the laser range finder. For example, the sonar data interprets long flat surfaces as convex, but the data from the laser shows them to be perfectly straight – implying the laser range finding is linear.

A custom mount holds both webcams and the laser line. As the cases of the webcams made it difficult to mount them, they had to be removed from their casings. One of the cams faces 25-degrees to the left, while the other faces 25-degrees to the right. That gives a 100-degree field of view to the bot. Both the cams are tilted upwards such that the bottom-line of their images is just below the horizontal.

The software processes the images and locates the laser line to calculate ranges. It makes 30 vertical scans from the top of the image looking for the laser line. Looking specifically for a laser line makes it simpler as the line is never vertical. Therefore, every point located on the line has a neighboring point.

Raspberry Pi Can Keep Your Plants Happy

Those who like indoor plants know how important it is to maintain a proper atmosphere for the plants to grow happily. Only a few parameters are important – air humidity, air temperature and soil moisture apart from adequate sunshine. However, it is rare for people to be able to monitor the health and well-being of their flora personally, given the busy schedules.

That is where a single board computer such as the Raspberry Pi or RBPi can help. Being flexible in setting up and connecting to the various sensors necessary, this SBC not only looks after the plants, but also alerts you with SMS and via email whenever the situation differs from the normal. This project also has an app, Plant Friends, for your Android phone, so that you are up to date on the real-time and historical parameter data on your plants. The project consists of three main components – the sensor nodes, the base station and the app.

You need a sensor node for each plant. Each of these sensor nodes consist of an Arduino clone called Moteino fitted with an RF transceiver, a battery meter, a temperature sensor, a humidity sensor and a sensor for soil moisture. The sensor nodes collect the readings from all the sensors and transmit the data using the transceiver to the base station. The sensors and the base station are connected via the 915MHz ISM band.

For this project, users must be slightly above the beginner level. Some basic experience with Arduino hardware and Arduino IDE will be necessary – for installing libraries, making LEDs blink, etc. Additionally, experience in wielding a soldering iron is also necessary. On the RBPi side, it is essential to be familiar with the basic knowledge of the SBC and with installing the Raspbian OS.

The Plant Friends system has several advantages. It reminds you to water your plants and sends you an alert via email and/or SMS. It works for multiple plants at the same time, even if they are in different rooms of your home. Since wires are a minimum and all components of the system are of a reasonable size, you can move the plants and the system freely about the home.

The entire system consumes low power and therefore runs on batteries. Typically, battery swaps are necessary every 4 to 6 months. The electronics is low-maintenance as it is housed in a moisture-proof enclosure. The best part of the system is the Android app, as it allows monitoring from anywhere in the world.

An RBPi, model B, is used for the project, although a model A will work equally well. However, model B has more RAM and an Ethernet port, which may be necessary for flexibility. A USB Wi-Fi adapter helps to connect to the internet.

For each sensor node, you will need a holder for four AA type rechargeable batteries. In addition, you will need a combined sensor for temperature and humidity. For sensing the moisture in the soil, you may use a soil probe consisting of a PCB with exposed traces. However, ensure there is no lead involved.

SLI: Sensing Without Touching

MEMS is revolutionizing technology, causing microminiaturization and increasing the precision of conventional solutions. Ubiquitous MEMS applications are emerging as the next most promising frontier by removing the need for touch in structured light illumination or SLI.

DLPs or digital light processors from Texas Instruments contain millions of mirrors. TI is pioneering SLI that works by projecting moving stripes of light onto objects. It then measures the deformities in the reflected patterns by reconstructing their 3-D shapes using algorithms. The biggest customers so far are OEMs that manufacture touch-free fingerprint scanners.

These scanners are different from the traditional, as they do not require the traditional ink-blotter protocol. Therefore, SLI is revolutionizing biometric, facial, dental and medical scanning by opening up a whole new frontier in DLP applications. That includes the entire range from scientific instrumentation to industrial inspection systems.

So far, TI already has OEM development kits with DLPs and algorithm libraries. These can recognize 3D shapes, contours, surfaces, discontinuities and roughness. Operating on light sources ranging from near-infrared to ultra-violet, they enable accurate, fast and non-contact 3D scanning and recognition systems.

With its new DLP LightCarrier development platform, TI will be using nearly half a million micro-mirrors for illuminating simultaneously almost anything with structured light. That will allow almost instant recognition and characterization of 3D objects without touching them.

For example, TI uses FlashScan3D in DLP technology to capture far greater detail of fingerprints with higher accuracy than any other SLI solution can. That helps in cutting down on the possibilities of technician error and fraud. Moreover, the new DLP LightCrafter can scan faster and store data internally as against on a separate storage device such as a laptop. Therefore, it helps in building even smaller and more portable SLI applications.

YoungOptics Inc. of Taiwan origin manufactures the DLP LightCrafter as a plug-n-play module for TI. YoungOptics also manufactures TI’s DLP Optical Engine for OEMs that make projection televisions. LightCrafter, along with TI’s DLP 0.3 WVGA chipset, is ready to be used by OEMs for research and development. However, it can serve as the main subsystem in their finished end-user products as well.

Along with the DLP chip that contains exactly 415,872 micro-mirrors is an ASIC or Application-Specific Integrated Circuit acting as a second custom controller. There is also a DVP or a DaVinci digital video processor with its own 128MB NAND flash memory for storing patterns, a configurable IO trigger for integrating cameras, sensors and other peripherals needed for SLI.

Users can optionally add an FPGA, thereby speeding up the SLI patterns that LightCrafter displays, making them faster up to 4,000 per second. Finally, LightCrafter is capable of generating 20 lumens of light as it has an integrated light-emitting diode array for generating red, blue and green light.

OEMs can also use embedded Linux for developing their software to run the DaVinci DVP in the LightCrafter. That makes it an evaluation module compact enough for integrating projected light for scientific, medical and industrial applications, creating faster development cycles for end equipment needing high-speed pattern display with a small form factor, intelligent and lower cost.

How do Sensors Measure Gear Tooth Speed and Direction?

Measuring speed of gears is an important factor in various industries, especially in pharmaceutical, tobacco, printing, woodworking, paper, textile, food and others where rotational machinery predominates. Gear speed measurements also necessary in pumps, blowers, mixers, exhaust and ventilation fans, wheel-slip measurement on autos and locomotives, flow measurement on turbine meters and many more.

The most common gear tooth sensors detect a change in the magnetic field for determining the speed and direction. Usually, these are of three types – the Hall Effect, magneto-resistive and the Variable Reluctance. There are optical types of sensors as well, detecting a change in light levels as the gear rotates past the sensor.

Sensors using magnetic properties are good for measuring speed and direction of gears made of ferrous metals. All these sensors are non-contact type and sensitive to detect the presence of gear teeth passing in front of the sensor. As a gear tooth comes close to the magnetic sensor, its output flips and the electrical level at its output changes state. The output remains steady as long as the gear tooth is within the detectors sensing zone. As the tooth passes out of this zone, the output flips back. Therefore, a magnetic sensor placed in front of a rotating gear, the output from the sensor will be a series of electrical pulses.

There are several advantages when using magnetic sensors. Apart from the sensors being non-contact type, they are robust, hermetically sealed and can withstand unregulated power supply. Most manufacturers make then RoHS and IP67 compliant. That means no lead or other toxic materials are used for manufacturing these sensors and dust or liquid will not enter their enclosure. That makes such sensors suitable for use in food processing industries.

For measuring the speed of gears made of non-magnetic material, engineers often use optical sensors. The most common sensor of this type is the optical interrupters. Gear teeth interrupt a light beam from an LED source and the detector produces a corresponding electrical output. A continuously rotating gear in front of the sensor therefore, creates a similar series of electrical pulses as the output from magnetic sensors do.

The functioning of optical speed or proximity sensors is dependent of the dust and dirt level of the environment where they are used. Therefore, their range of applications is somewhat restricted as compared to magnetic sensors.

Measurement of direction involves a reference point, which means two sensors need to be used, with one of them being the reference sensor. An electronic circuit measures the time gap between the responses from each sensor. As the gear tooth passes in front of both sensors, one of them will change output before the other. If sensor A happens to trigger before sensor B does, the electronic circuit determines the gear is moving from A towards B. In case the output of sensor B switches before sensor A does, then the gear is moving from B towards A.

Usually, the sensors provide separate digital outputs for speed and direction. Their measuring capability may extend from detecting near zero speed up y 15 kHz.

How do Sensors Measure Angle?

An angle is the degree of rotation of an object from a reference position about a central axis. In the engineering world, there are two types of angles requiring measurement. One is the physical or mechanical characteristic, such as the rotation of a shaft with respect to its bearing or housing. The other is a mathematical term such as the angle between two phases of alternating voltage system. Usually, sensors measure angles in a format that a computer or a machine can understand, interpret and utilize.

It is also a common practice to convert a physical characteristic into a rotational mechanical movement to measure linear displacement. For example, the distance traveled by a shaft can be translated into rotational movement by a rack and pinion arrangement. The angular position sensor attached to the arrangement then interprets the angular movement in proportion to the linear movement of the shaft.

In the market, you will find different sizes and forms of angle positioning sensors using various technologies. Generally speaking, these sensors are versatile and one can use them in all kinds of applications, such as in agriculture, commercial equipment, off-road vehicles and in automotive industries. Most of the applications above require a product suitable for operating in harsh environments, including moisture, dirt, dust, extreme temperatures and more.

For example, Forklift Position sensors measure the angle of the forks on a forklift truck. According to OSHA, one of the primary causes for tip-over accidents on forklifts is excessive speed when the machine is turning or rounding a corner. The angle position sensor on the truck helps it to remain within a safe speed and prevents overturning. This particular application also prevents accidents from unbalanced loads and limits the operation of the machine when the load is improperly positioned or balanced.

The simplest form of measuring angle is by using the gear tooth sensor. By sensing the teeth to count the rotation of a gear or wheel, engineers monitor and limit speed. Another common form of angular position measurement utilizes potentiometers. Other more sensitive and rugged types of angle sensors use optical or magnetic technology.

Traditional rotary encoders use an LED transmitter, a coded disc and a photo sensor to detect angular movement. The disc is coded with opaque and transparent sections, which transmit light in a specific manner to the photo sensors depending on the position of the disc. The photo sensor converts the light falling on to it into an electrical code. This allows the encoder to detect rotation, position, angle, etc.

Sensors that are more rugged use the Hall-Effect technology for measuring angle. This technology uses magnetic field sensing and does not require the critical positioning necessary for the components using optical methods. In both methods, accuracy of an angle sensor depends largely on its resolution. The higher the resolution, the more precise is the detection of angular movement. Sensors measuring angles using Hall-Effect technology can perform without physical contact, thereby remaining unaffected by vibration and abrupt movements. These sensors also have the added benefits of virtually unlimited lifespan.

Wireless sensors sans batteries

The Internet of Things has led to several simple sensors being used for applications requiring reporting of their readings wirelessly to a gateway or hub. However, most sensors require to be powered from batteries, creating logistical and cost barriers to several use cases. Now, many wireless sensor modules appearing on the market do not require batteries, as they are ultra-low power types.

Several key building blocks are necessary to make up a wireless sensor module meant for IoT use. The first among these is the sensor itself, its signal feeding a micro-controller that processes and packages it for transmission. The final part consists of a radio transceiver to send the information to its destination. Even with the most careful logic design, these building blocks work at a minimum of 1.8V, using up several tens of microamperes at modes requiring the lowest power.

However, in the last decade, extensive research has resulted in development of sub-threshold circuits involving logic, memory and RF. Transistor switching, in conventional logic design, takes place between saturation and an on-off state, dominated by leakage currents. Switching mostly occurs at a gate-to-source voltage or VGS of about 0.5V, which is the threshold voltage or VT for the transistor. In conventional logic, VGS < VT, is the condition for the transistor to remain in the off state. Sub-threshold circuits use this off-state region for the two operational states of a transistor. With the transistor's gate voltage operating below the threshold, the supply voltage can go lower than the conventional 1.8V. An active logic circuit consumes power relative to the square of the supply voltage. Therefore, operating at lower supply voltages can mean considerable power savings. The drawback in this manner of operation is that switching speeds slow down – but that does not hamper many applications. Another requirement of sub-threshold circuits is that a careful control is to be exercised on device physics, including circuit structures. These are necessary to mitigate the effects of temperature variation and noise. However, researchers have provided answers for these problems as well and the solutions have proven themselves practically. Functioning circuits are available for analog, microprocessors and memory devices. Sub-threshold designs are now starting to appear in the market as full SOCs. Universities of Michigan, Virginia and Washington have culminated their research efforts as a two-year old startup, PsiKick. They are preparing a sub-threshold circuitry based wireless sensor module that will operate without batteries. Aside from the RF transceiver, a micro-controller and a sensor front-end, the module will include blocks for energy harvesting. This makes it a self-powered sensor platform that can be used in a wide array of applications. Another design, a second-generation version, is on the cards. This is based on standard CMOS technology and a demonstrable product is due any time soon. The sub-threshold module requires astonishingly small power to operate. Compared to sensor platforms currently available, these modules will consume 100 to 1000 times less power. When fully operating, the micro-controller consumes only 400nW while the RF transmitter generated 10µW, which is effective within a 10m range. The module operates within a supply voltage range of 0.25 to 1.2V. That makes the module eminently suitable to the output capabilities of most energy harvesting methods.