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Proof of concept for the use of wearable sensors to monitor women and men's workload and mobility in Indonesian agricultural communities

  1. Proof of concept for the use of wearable sensors to monitor women and men’s workload and mobility in Indonesian agricultural communities Tim Stewart, Rachel Davey, Giulia Salmaso, Dipo Pangestu & Sander van Berlo
  2. Pro-poor growth & access to life-enhancing products/services •Poor women and men cannot influence •Work beyond the poor to achieve change in relevant market though facilitation with market players Changes result in growth /or access to life-enhancing products/services for poor women and men •The poor exist in market systems which are dynamic and interconnected •The poor are affected by changes in market systems (+ & - ve) Conventional, direct responses miss this link... Reducing poverty as a result of increased incomes & or access to life- enhancing products/servicesPoverty Reduction Market System Change Systemic Intervention Market systems development
  3. Poverty Reduction Pro-poor growth & access to life-enhancing products/services Systemic Intervention • MSD programmes work in partnership with third parties (private & public sector) – not directly with farming HHs • Impact is dependent on the actions of these partners • Therefore challenging to observe impact on women and men of a change in their livelihood – e.g. on work-load The challenge of reaching women in MSD • Economic advancement • Access to opportunities • Access to assets • Decision making • Manageable workload
  4. • DFAT Australia-Indonesia Partnership for Rural Development • Irrigation component aimed to improve access for 10,000 smallholders & increase incomes by 60% • Worked with rice millers & irrigation entrepreneurs • Improved infrastructure & service provision • From 1 to 2 or 3 rice seasons – increasing yields & incomes Improving access to irrigation for small rice farmers
  5. ?...
  6. Aims of the research to examine the feasibility of using activity wearables and smartphones to quantify relative workloads and activity patterns of women and men rural farmers in Indonesia.
  7. Innovative approach
  8. Data collection
  9. Results – mobility 0 0.5 1 1.5 2 2.5 3 Preparation stage 2 Harvesting Vegetative stage Preparation stage Average number of visits per day Woman Man Farm 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Preparation stage 2 Harvesting Vegetative stage Preparation stage Average number of visits per day Woman Man Home
  10. Results – mobility
  11. Results – mobility 0 20 40 60 80 100 120 140 160 180 120 140 160 180 200 220 240 260 Travelradius(km) Day number, 2018 Travel radius, all stages Man Woman
  12. Results – average time spent Farm Home 0 20 40 60 80 100 120 Preparation stage 2 Harvesting stage Vegetative stage Preparation stage Average time spent (min) Woman Man 0 100 200 300 400 500 600 700 Preparation stage 2 Harvesting stage Vegetative stage Preparation stage Average time spent (min) Woman Man
  13. Results – workload Farm Home 80 82 84 86 88 90 92 94 96 98 Preparation stage 2 Harvesting stage Vegetative stage Preparation stage Heart Rate (bpm) Woman Man 76 78 80 82 84 86 88 Preparation stage 2 Harvesting stage Vegetative stage Preparation stage Heart Rate (bpm) Woman Man
  14. Results – workload
  15. Results – trend analysis Farm Home Other Male Female
  16. Results – daily timeline A day in the life of: Couple 17 2018-05-26
  17. Conclusions Limitations comparing with programme’s standard survey – but confirmed overall perceptions (except for mobility) helpful for improving design of future surveys. Observed the “triple burden”. Successfully demonstrated the potential of measuring workload objectively, and activity patterns of men and women rice farmers. Use of wearable devices, GPS tracking and smartphones has potential to monitor the impact of changes in agricultural practice or policy at the individual, household or community level.

Editor's Notes

  1. Tim Stewart, Palladium Acknowledge my co-authors and the support of DFAT.
  2. Entry Market Systems Development is an approach used by a number of donors (e.g. DFAT) and implementers (Palladium & Swisscontact) around the world to create sustainable poverty reduction at scale. Main MSD places poor women and men within relevant market systems (e.g. agriculture) Poverty is reduced through increased income and/or access to life enhancing goods and services that result from changes in market systems MSD programmes aim to facilitate this change by working with legitimate, sustainable actors – private and/or public sector – to improve inclusiveness and competitiveness Exit ….
  3. Because MSD programmes work with and through third parties – and not directly at the household level – it can be difficult to observe changes in livelihood on individuals in the household: Economic advancement – increased income Access to opportunities and life chances such as skills development or job openings Access to assets, services and needed supports to advance economically Decision-making authority in different spheres including household finances Manageable workload
  4. Entry AIP Rural was a DFAT MSD programme in Eastern Indonesia, Managed by Palladium in partnership with Swisscontact Phase 2 just commenced – called PRISMA Main Irrigation component Worked with rice millers, irrigation entrepreneurs, pump retailers, engineers, and other service providers To improve infrastructure and provision of irrigation services. And incomes of rice Exit Mainly East Java – Bojonogoro district & two others
  5. Entry Obtaining accurate data on women and men’s workloads is difficult Relies mainly on qualitative recall studies – focus groups, time use dairies, recall Subject to inaccuracies and bias Even developed countries find this challenging – and rely on qualitative methods – e.g. American Time Use Survey. Main Pondering this on the bus one day Reading the local newspaper Saw an article about a study that UC were doing, recruiting fitbit wearers to provide data to look at activity levels and the urban environment Exit Emailed – went for a coffee with UC and Onmi Design Put a plan together that DFAT were happy to support
  6. This study aimed to examine the feasibility of using activity wearables and smartphones to quantify relative workloads and activity patterns of women and men rural farmers in Indonesia.
  7. Entry 1st we did a LITERATURE REVIEW: Main A total of 68 studies were analysed - Most of the studies identified used qualitative, descriptive methods to examine gender differences in occupational workload and physical activity patterns. Very few studies used objective measures to examine the workload or division of labour and None were found using smartphones and activity wearables. Exit We therefore believe this is a first!
  8. Entry The next step was to - Conduct an Ethics review Conduct a pre-feasibility study with staff – to test the technology, mobile reception etc Main Recruited 30 households – 30 women and 30 men participants in a village called Besah Trained them in how to use the Garmin devices and the smart phones Monitored them through out one and a bit agricultural seasons (April – September 2018) All data anonymized
  9. Entry – results mobility We were able to observe the mobility of women and men – how often, how far, and for how long they went to various places Main Men have a higher frequency of visits in all three categories (home, farm and other). Men travel around more and between places than women. Men and women have similar behaviour in the different stages; they visited the farm the most in preparation stage 1, the second most during harvesting, and the least during the vegetative stage. Men visited about 5–6 ‘other’ places each day. Women visited about 2–3 ‘other’ places each day. Throughout all farming stages, the men visit the farm more than women.
  10. Entry - DISTANCE This image shows the travel radius by participants from the center of Besah village in harvesting stage Main Women have a bigger average travel radius than men in the preparation stage 1 and harvesting stage. During the preparation stage, women’s average travel radius is 5% bigger than men’s. During the vegetative stage, men’s average travel radius is 41% bigger than women’s radius. Especially during the harvesting stage, women’s average travel radius is 67% bigger than men’s. THIS WAS A SURPRISING FINDING May have been related to religious festivals and family visits During preparation season 2 men’s average travel radius is 24% bigger than women’s.
  11. Mobility Continued… FREQUENCY This image provides additional insight into the travel behaviour of the study participants: Men make more frequent trips than women, but often do not travel further than approx 26km. This could be to the nearby town Bojonegoro. Men and women also travel together when making a longer trip e.g. 95km travel radius. Women also make trips by themselves and appear to travel further get to these destinations compared to men.
  12. Entry – TIME SPENT This shows the time spent in the home and farm Women spend more time at home than men, regardless of the stages i.e. 30-50% more at home Preparation stage 1: 50% more, Vegetative stage: 42% more, Harvesting stage: 40% more. Preparation stage 2: 34% more. The average time spent in the home is statistically higher among women, compared to men
  13. Entry - WORKLOAD This shows workload - The measure of heart rate has been used as a proxy for workload estimation. Both men and women have higher heart rate levels at the paddy field than at home, which is what might be expected since more heavy labour is done in the fields. Women appear to have higher average heart rates than men during the preparation and vegetative stages of the agricultural cycle. This may reflect peak planting when women are busier in the fields than men (transplanting rice), whilst during the harvesting stage, men are busier in the field than the women. Also women seem also to be much more active at home at this time
  14. Workload Continued… Based on statistical analysis, HRw does not differ significantly among men and women in the different categories of ‘light’, ‘moderate’ ‘heavy/vigorous’. Female farmers exert working intensities that are comparatively similar with their male counterparts and are not significantly different. However, women undertake higher physical activity work rates in the home (possibly due to domestic chores and looking after family)
  15. Entry – trend analysis Data visualisation techniques are used to make sense of the data and allow to make visual observations Each circle represents data from 1 Phase of a season for one couple (vegetation left, preparation right), presented on a 24-hour clock The woman’s data is plotted within the smaller inner circle and the man’s data in the outer circle; the black line separates the two. The woman (green circle) and man (purple circle) represent activity data from Garmin, a high opacity means the behaviour is more frequent. The background colours represent locations, orange is the ‘Home’ and blue is the ‘Farm’. Grey surfaces represent ‘other locations’ and white indicates missing data. Diagonally striped surfaces indicate sleep time and duration. Some observations: During vegetative stage both man and woman spend time at the farm between 09.00 and 12.00. The man often has higher intensity activity in the morning and less after 12.00. The woman’s activity is also of higher intensity in the evening from 21.00 During preparation stage 2 the man spends much longer periods of time at the farm
  16. Entry Whilst the previous slides present data for all participants that have been aggregated to examine averages and general trends in workload and activity patterns/mobility, the real benefits and advantages to using the wearables and smartphone technology is being able to monitor at an individual level (providing very detailed measures for individual farming households). The advantage is the ability in future to monitor the impact of changes in agricultural practice or policy at the individual level. To illustrate the utility of using the Smartphone and Google GPS location process at an individual and household level, the following case studies have been included. Timelines of activity and location can be devised that give a detailed picture of activity patterns throughout the day. The following timelines depict activities for both men and women for ONE households
  17. Entry - Conclusions A direct comparison with the standard survey instruments wasn’t possible – some questions didn’t tally, & they were not repeated at the same key stages throughout the season. However the overall trends observed did largely square with the key observations and perceptions of the programme team – except for mobility (surprised to see how much more mobile women are than men). Triple Burden observed: Women on average spend similar amounts of time during the day in heart rates in the ‘light’, ‘moderate’, ‘vigorous/high’ categories as men. Women also undertake considerably higher physical activity work rates in the home compared to men, thus supporting the ‘triple burden concept’. The relative workloads (heart rates) and activity patterns (GPS monitoring and step counts) of women and men could be monitored and quantified at both the individual, household and community level. Although gender workloads differ depending on cultivation stage, initial findings show that overall, women exert heart rate intensities/workloads that are similar to men. In terms of testing the use of IT wearable devices, smartphones and apps’, this feasibility study has successfully demonstrated the potential of measuring objectively and in ‘real-time’ workload and activity patterns of men and women rice farmers over a 5-month period of the agricultural cycle. Uptake and adherence to wearing the activity monitors and using the smartphones and apps’ was extremely high and acceptable to both men and women rural farmers in Indonesia. FURTHER USE The novel use of smartphones and wearable sensors has the potential to make direct objective, empirical observations of respective work load and activity patterns and locations in ‘real time’ and to monitor the impact of: Changes in policy/practice on work load/work patterns on men and women farmers. This could also be used for comparison of sub-populations or communities from different regions or countries. Can also be used to calibrate conventional methodologies
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