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Pasco wireless sensors and Smart Cart

PASCO and Smart Cart equipmentGreen Tick Reviewed: Pasco wireless sensors and Smart Cart
Resource type: Wireless senses
Company: Pasco
RRP: From £35.82 to £91.63 for the sensors and £146.61 for the Smart Cart
Link: Available from Scientific & Chemical Ltd

Pasco has introduced a range of white wireless sensors to provide a mobile and cable-free solution, particularly useful for schools making use of mobile technology such as tablets, smartphones and Chromebooks. The sensors link to SMARTvue software, which can be installed at no cost on iOS, Android and Google devices. Existing Pasco blue-cabled sensors can also be linked to this system using an ‘AirLink’ interface. 

This review of Pasco’s wireless sensors is in four parts:

  • Wireless sensor range, describing key features of each sensor, and general comments on their operation
  • SPARKvue software for linking to the sensors, allowing the display, analysis and storage of data collected
  • System in operation, outlining several activities to illustrate how the sensors and software could be used in science teaching
  • Conclusions, including recommendations, strengths and weaknesses of the Pasco wireless system

Wireless sensor range and Smart Cart 

Name

Cost of wireless sensor (cost of non-wireless)

Power source

Measurement

Wireless Temperature


£35.82 (£27.49)

CR2032 replaceable battery

-40 - +125 oC +/1 0.5 oC, resolution 0.01 oC
(the housing should not be exposed to extremes of the temperature range)

Wireless Light (ambient and spot)

£ 50.81 (£ 54.14)

CR2032 replaceable battery

Ambient light sensor:
UVA 0-100%, UVB 0-100%, UV index 0-12, Illuminance 0-131 000 lux, PAR (photosynthetically active radiation) 0-2400 micromoles/metre2/second, Irradiance 0-1362 watts / metre2
Spot light sensor:
White 0-100%, Red 0-100%, Green 0-100%, Blue 0-100%

Wireless pH

£ 54.14 (£ 73.30)

CR2032 replaceable battery

0-14 +/- 0.1, resolution 0.02

Wireless Conductivity

£64.14 (£ 101.63)

CR2032 replaceable battery

0-20 000 microsiemens / centimetre
Total Dissolved Solids milligrams / litre

Wireless Voltage

£ 44.98 (£ 91.63)
inc USB cable and red, black connecting leads

Rechargeable battery (via USB)

+/- 15 v

Wireless Current

£ 44.98 (£ 73.30)
inc USB cable

Rechargeable battery (via USB)

Ranges +/- 0.1 A and +/- 1.0 A

Wireless Pressure

£ 64.14 (£ 82.47)
inc USB cable, plastic syringe, plastic tubing and connectors

Rechargeable battery (via USB)

Pressure 0-400 kPa, resolution 0.1 kPa

Wireless Force - acceleration

£ 91.63 (£ 101.63)
inc USB cable and hook, rubber pad and attachment screw

Rechargeable battery (via USB)

Force: +/- 50 N
Gyro:  Angular velocity in X, Y and Z planes up to +/- 2000 degrees per second
Acceleration:  X, Y, Z planes and resultant up to +/- 16 g

Wireless Smart Cart

£ 146.61
inc USB cable and hook, rubber pad and magnetic bumper

Rechargeable battery (via USB)

Force: +/- 100 N
Position
Velocity: +/- 3 m/s
Acceleration: X, Y, Z planes and resultant up to +/- 16 g (g =9.8 m/s2)
Gyro:  Angular velocity in X, Y and Z planes up to +/- 2000 degrees per second


Construction: The sensors are made of rigid white plastic, and held together by tamper-proof screws. The impression given is that these are solid, well-made devices that will easily withstand the rigours of classroom use. 

Battery replacement: Battery access is either via a cover that unscrews using a coin, or, in the case of the light sensor, a draw-and-catch mechanism. Pasco suggests that the battery should last for a year in normal use. Rechargeable batteries have an ‘expected life of 3-4 months’ usage on a single charge with normal use’, or 11-70 hours of continuous use depending on sample rate chosen. 

Controls: Power on/off switches are small and recessed to avoid accidental operation. Each sensor uses LEDs to indicate battery or charge status and Bluetooth connection status. Power is turned off automatically if not in use.

Fixing: Wireless pressure, light and force – acceleration sensors each have attachments for fixing to standard laboratory boss / clamp fittings.

Remote recording: All the sensors reviewed can display measured values in ‘real time’ on the screen of a paired device. All except the Smart Cart (i.e. all those with ‘wireless’ in their names) can also collect data remotely for downloading later.

Connectivity: The sensors use low energy Bluetooth (BLE) to connect to other devices. This limits the distance between sensor and display screen to a quoted maximum of 10 metres, which was found to be accurate when measured outdoors. The benefit of BLE for learning science is that sensors can connect independently of a wireless network, allowing them to be used both indoors and outdoors.

Support Each sensor comes with a sheet explaining how to get started, and contains a link to the sensor-specific online Reference Guides.There are video guides available via the Pascoscientific YouTube channel for most wireless sensors: temperature, pH, pressure, force – acceleration, voltage and Smart Cart. Pasco also provides an effective personal support service for technical issues.

SPARKvue software 

Installation: SPARKvue is available as a free download for iOS, Android and Chromebook, and available at low cost for Windows and OSX devices. Although the file size is large (over 170 Mb), installation is straightforward and presented no problems when tested with phones, tablets and a Chromebook. Most of this review was conducted using an iPad mini and iOS smartphone with SPARKvue 2.6.0. (Chromebooks and laptops require an additional BLE dongle, costing around £ 10, enabling the laptop to access BLE).

Functions: The SPARKvue app is used to collect, configure and display data. It comes with 17 experiment guides, which make use of wireless and other sensors and provide guidance on how to set up and run data collection in familiar contexts, such as diffusion, fermentation and calorimetry. Additional ‘SPARKlabs’ are available for free download.

Two templates are also provided to demonstrate how data can be collected in tables and then displayed as a bar graph or line graph. The experiment notes are well produced, contain clear explanations and instructions, demonstrate how to set up data collection, and include quizzes to test understanding.

The software can access internal sensors in the mobile device (camera, microphone, accelerometer) without needing to link to external sensors. Accessing data from the microphone provides an easy way to develop confidence with the software before attempting to link to external sensors. Linking to external sensors was found to be very straightforward, and is dealt with in the next section.

Once data has been collected, it can be displayed on screen as a line graph, table, numerical value or meter reading by changing the page display. Tools are provided for basic analysis, such as slope (gradient), curve fit, and statistical analysis. A calculator is provided for further analysis if required, and there is a ruler tool for measuring parts of a photograph, which is a very useful feature when investigating motion.

The graph display is easy to use. It can be rescaled by dragging digits on the axes, and it allows multiple runs to be displayed on the same graph. It is also possible to display different parameters by adding a vertical (Y) axis to an existing graph, or changing the horizontal (X) axis from time to some other variable. This is particularly useful when assessing correlation between two variables.

Data can also be displayed as a bar graph – essential when collecting discrete data – but the method for doing this is not intuitive. Video instructions are provided on the Pascoscience YouTube channel, and these are essential viewing for anyone wishing to fully understand the features of the app.

Users can create a journal of their investigation by adding pages, taking snapshots of pages, inserting videos or photographs and adding notes. Data and journals are saved in the same way, either internally to the device or using the Pasco cloud-based service. Data can also be exported to other apps on the device and to various cloud storage facilities.  

A key feature of this app is that it allows sharing of data with other devices. The user can control which other devices, within BLE range, are permitted to access the host device and then, in ‘guided’ mode, the shared devices can see the same data on their screens, but cannot control data collection. These shared devices can then perform their own processing and analysis functions, and save their own copy of any changes. 

The Pasco Wireless system in operation 

Linking to external sensors: No changes to device settings are needed for successful linking. The Bluetooth button in the app lists the sensors in range. If there are multiple sensors, they can be identified by a six-digit number that is clearly displayed on the body of the sensor. Selecting a sensor allows either remote data collection to be configured, or real time data collection via the pre-formatted graph / table / digit / meter pages. If the sensor measures several variables, the required variable can be selected by tapping on the graph axis. Measurement frequency and units can also be selected. Default data collection is continuous (periodic), but this can be changed to manual allowing discrete readings to be taken.

Activities: The following activities show a range of uses of the wireless sensor system, to illustrate many of the features of SPARKvue software.

Activity 1: Measuring the cooling effect of aerosol sprays

This activity uses a single sensor and the real time line graph function to compare two data runs and measure a change in the value of the variable measured.

The temperature sensor was turned on, and linked to SPARKvue. In the first data run, an aerosol muscle freeze spray was sprayed onto the tip of the sensor five seconds after switching on data collection, for two seconds’ duration. On the second data run, a similar procedure was carried out using a muscle warming aerosol spray.

The graph shows a section of the blue curve that has been selected, and the co-ordinates tool shows that there was a cooling of 20.7 oC over five seconds.

Activity 2: Is there a correlation between pH and conductivity?

pH and conductivity sensors were placed in sodium hydrogencarbonate solution before citric acid was added in small quantities. Data were collected ‘manually’ once each addition of citric acid had dissolved. The data were then displayed as a line graph, with pH on the vertical (Y) axis and conductivity on the horizontal (X) axis.

The data show a linear relationship between pH and conductivity up to a pH of 7.0.

Activity 3: The relationship between pressure and volume

The wireless pressure sensor is supplied with a large plastic syringe, plastic tubing and connectors. Linking these together enables pressure readings to be taken for fixed volumes of air. The process involved in creating a graph of pressure against volume is slightly more complex than in Activity 1, as the volume data (read off from the syringe barrel) need to be entered manually into the results table, and the resulting graph configured to show pressure against volume rather than pressure against time. 

The collected data are shown as brown dots connected by brown lines. The red curve is a curve of best fit added using the curve fit tool (inverse fit).

Activity 4: Using the Smart Cart to understand distance – time and velocity – time graphs

The Smart Cart is a robust plastic dynamics trolley with built-in sensors for measuring a wide range of parameters. It is possible to connect a wireless force – acceleration sensor to other dynamics trolleys and collect similar data (excluding position and velocity), but this would also miss out on several other advantages of using the smart cart:

  • It is provided with rubber and magnetic bumpers to investigate elastic and non-elastic collisions
  • The spring-loaded plunger can be set to different loads 
  • There are numerous attachment points for connecting sensors or other equipment to the smart cart, and there is a tray provided for adding additional masses
  • The quality of manufacture is superb, ensuring that the wheels rotate virtually free of friction. 

Whilst the Smart Cart does not collect data remotely, unlike the wireless force – acceleration sensor, it is difficult to imagine a scenario where this limitation would be a problem. Smart Carts are available in blue and red plastic for easy identification in collision experiments. 

In this activity, the smart cart was used to follow a predicted curve on a line graph for position (distance) and for velocity. 

The Smart Cart was linked to SPARKvue, and position chosen as the selected variable to be measured. Using the prediction (freehand) tool, a line was traced from the graph origin. When data collection was started, the challenge for the user was to propel the smart cart on a flat surface so that the motion of the cart matched the path of the prediction line as closely as possible. This was then repeated for a graph of velocity against time, which proved far more challenging to match the motion of the cart with the velocity prediction. The purpose of this activity is to help students understand how to interpret the shape of distance – time and velocity – time graphs. 

In this graph of distance –time, the fine orange curve was drawn freehand using the prediction tool, and the wider brown row of dots shows the position of the Smart Cart trying to ‘mimic’ the prediction curve.

 Activity 5: Bird feeder action

The remote logging function of the wireless force – acceleration sensor was used to monitor bird feeding activity levels, rather than watching out the window to see when garden birds visit the bird table. A bird feeding column was filled with peanuts and suspended from a wireless force – acceleration sensor, which was attached to a bird table. The sensor was linked to the SPARKvue app, so that the recording interval could be specified, and then the sensor recorded data remotely until stopped. 

On reconnecting the sensor to SPARKvue, the software presented the option of downloading and presenting the logged data. 

The graph shows a gradual upward trend as the mass of the bird feeder decreased over the six hours that data was recorded. The force measurement changed from -5.3 N at 0.5 hours to -4.7 N at 6 hours, equivalent to a mass of 60 g of peanuts consumed. The rate of decrease was slower in the last hour, when birds had stopped feeding. Birds were feeding most actively between 0.75 hours – 1.5 hours (11.15 – 12.00), as can be seen from the steeper graph gradient and by the cluster of downward spikes.  Each downward spike is caused by one or more birds landing on the feeder, and upward spikes when they take flight from the feeder.

Activity 6: Comparing the photosynthetic activity of different light sources

Incandescent electric light bulbs have been replaced by more energy-efficient types of bulbs including light-emitting diode (LED) bulbs and compact fluorescent lamp (CFL) bulbs. Seedlings grown under a combination of LED and CFL lamps of similar power output tend to grow towards CFL bulbs. This activity uses the wireless light sensor to compare the output of the two bulb types to provide evidence for explanations of this observation. 

The wireless light sensor can measure several different factors as shown in the sensor table. In this investigation, a comparison was made between the red (R), green (G) and blue(B) outputs of the two types of bulb, and the photosynthetically active radiation (PAR) values. The activity involved taking a manual (i.e. ‘one off’) reading for the different parameters for each bulb and entering them in a table. The resulting bar graph was rather complex and, to allow the editing of position and colour of the bars, the data were exported into a spreadsheet before being captured as a screen grab and reimported into the SPARKvue journal. The following image shows the imported bar graph: 

As shown in the figure, the LED bulb emitted about the same percentage of blue and green light as the CFL bulb, and slightly more red light. However, the CFL bulb emitted a much higher level of photosynthetically active radiation (PAR), which could explain the phototropic response described above.

Conclusions 

Pasco has produced a very powerful and well-made set of tools for conducting a wide range of science investigations suitable for all phases of science education. The ability to link sensors directly to any mobile technology device or computer, with free software, provides a very cost-effective way to provide pupils with rich practical experiences.  Similar products are available that use existing wireless networks for communication, but Pasco has chosen to use a version of Bluetooth instead – a solution that frees up reliance on networks, but does impose other constraints. As with most technology purchases, prospective buyers need to weigh up their own circumstances before committing to a specific solution, but I would have no hesitation in recommending this system, particularly if ‘starting from scratch’.

Pros

  • A very cost-effective solution:
  1. No data logger is required, as sensors link directly to mobile technology devices or computers (which do need an additional dongle)
  2. Wireless sensors are currently significantly cheaper than their wired equivalents
  3. Free software, which can be installed on any mobile device, and used with a mixture of devices within one session
  4. The output from one sensor can be shared with other devices in the class. 
  • Well-made robust sensors, some of which record a wide range of parameters within one sensor, and which have either good battery life or are rechargeable. All the wireless sensors can record data remotely. Previously a data logger would be required to perform this function. 
  • Independent of network constraints, and therefore does not interfere with other components within a network environment; requires no network installation; and can be used either inside or outside for fieldwork. However, Bluetooth does impose a maximum range of 10 m between sensor and receiver, and is limited in the number of concurrent connections that can be made. 
  • The system can grow as a user gains confidence, from modest initial use to more complex advanced features, use for analysis, creating ‘experiment guides’ or writing experimental journals. Capstone licensed software provides even more advanced analysis tools and uses the same sensors. 
  • Good levels of advice and guidance are available, both as online manuals, and YouTube explanatory videos. There is also a good e-mail teacher support service if needed. 

Cons

  • Although basic functions such as linking to a sensor and recording some data are intuitive, more advanced functions do need the investment of time to build familiarity and confidence, as SPARKvue is a fully featured software tool.
  • The addition of a power meter function in the software would be helpful to identify when battery replacement or recharging of the sensor is needed.
  • Currently there are nine different wireless sensors available. A commitment to add to this range would be helpful before a school invests in the replacement of their existing (cabled) sensor system. This is less of a problem for existing Pasco customers, as earlier sensors can be linked to SPARKvue via a Bluetooth ‘AirLink’ interface.