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  • Hello Crowd Science, it's Saugat Bolakhe here from  Nepal. My question actually revolves around the  

  • most burning issue of this decade that is climate change.

  • This is Crowd Science from the BBC World Service with me Marnie Chesterton.

  • We're here for  your science questions.

  • We are under climate crisis

  • and I am a complete supporter of climate movement  but some reports claim even if we stop emitting  

  • these greenhouse gases today the temperature will  still rises for maybe 40 years or more.

  • That means we are eventually destined to an unstable climate  and future.

  • What are our preparation, what kind of climate smart and adaptive technology

  • have been going on in this world recently?

  • Saugat's question is timely the UN body for assessing  climate science - the IPCC - has released a report

  • warning that we humans are causing irreversible  damage to the planet.

  • And Saugat should know. He wrote to us from Nepal which has seen an  increase in wildfires and drought in recent years.

  • The monsoon season there has become less and less  predictable which makes it harder for farmers to  

  • know when to plant crops or harvest them. Of course  it's not just Nepal, here in Europe we're seeing  

  • the effects of climate change on weather patterns  too with devastating floods in parts of Germany,  

  • Belgium and the Netherlands.

  • Meanwhile over in  the US, wildfires now seem to be an inevitable part of life.

  • The IPCC has modelled future  scenarios and says that the worst future -

  • the one with more droughts more floods and millions displaced as their homelands become uninhabitable -

  • the way to prevent that version is to stop putting more greenhouse gases into the air

  • and fast. Of course we could all try to not fly, not to drivegasoline-powered car and not to eat meat

  • but this is about more than personal responsibility. This needs big changes to the way our societies operate.

  • We're unlikely to go back to pre-industrial existence. Life without electricity?

  • How would you listen to Crowdscience? Unthinkable.

  • Since life is getting more and more digital maybe we could harness some of the potential

  • of our tech savvy lifestyles to help reduce our emissions.

  • Ideally without rebuilding the homes  and cities we've already constructed,  

  • or causing too much effort to people like me who live in them. Wouldn't that be smart?

  • Well in today's show we're going to investigate three  areas where smart tech might just be able to help.  

  • First though let's look at what's producing most of the greenhouse gases.

  • Generally speaking the direct emissions come from transport, from  buildings, from industry and from agriculture and  

  • forestry.

  • That's Professor Srinivasan Keshav from Cambridge University

  • explaining that we humans are responsible for emitting around 40 billion tons of co2 into the atmosphere every single year.

  • And co2 or carbon dioxide is the most  common of the greenhouse gases. It might  

  • surprise you to know that Keshav isn't a climate scientist, he's a data guy. You might be thinking  

  • what does computer science have to do with global warming? Well Keshav's one of a growing number of  

  • people using clever computing to help us cut our carbon emissions in all sorts of ways.

  • So listener Saugat is right on the money.

  • A recent report that  came out from the World Economic Forum identified digital technology as

  • being probably the world's most powerful influencer to accelerate action to stabilise global temperatures below two degrees.

  • And other people identify the digital sector as having the potential to reduce fossil fuel emissions to 15% by 2030.

  • And it comes from the fact that we can use digital technology to make things  more efficient.

  • This idea of efficiency is key as we'll hear throughout this show it means we don't need to build a new environmentally friendly world  

  • from scratch we just need to use what we have but  better. When I say what we have I'm talking about  

  • the infrastructure, the transport network, the power  grids, the buildings, all of it can be made to work  

  • much more effectively saving precious energy. So let's start with the sector that actually produces  

  • the energy because currently it's responsible for more than 70% of our greenhouse gas  

  • emissions. That includes the energy that powers big industry, heats and cools our buildings  

  • and fuels our cars. It also powers the tech that aims to radically reduce those emissions

  • I mentioned smart technology earlier and you may be  wondering what makes any of the new developments  

  • we'll be discussing smart. Keshav says it's a term to be taken with a big dose of cynicism.

  • Smart is a marketing term you know. It doesn't really mean anything if I say I have a smart  

  • home, that means everybody else has a dumb  home, obviously? Right so if anybody says  

  • they have a smart anything I would say you know look twice, they're probably trying to you know.  

  • Whack an extra 50 dollars on the price of your whatever it is?

  • Exactly. At some level smartness has to do with the incorporation of digital technologies into the

  • system so it's somehow responsive to your wishes and to your presence. So yes calling something

  • smart might just be a way of selling us more stuff but it's still useful as a way of describing

  • how much more reactive things can be to our needs when artificial intelligence is built in.

  • Keshav uses an example of a home heating system to explain how.

  • It is on the risk for you to keep  changing the temperature when you leave home and you come back home etc

  • or a smart thermostat. What they do is they observe that you typically leave home around 9.00 am

  • and you typically come back around 5. All right let's go and change the temperatures

  • and without you having to do anything  it becomes responsive to your occupancy.

  • Smart thermostats like the one Keshav's talking about  are common place these days.

  • Maybe some of you have even got one in which case well done you're almost  certainly using less energy to keep warm but don't feel too smug yet

  • because if that home heating  system is powered by fossil fuel - and globally most heating systems are -

  • then both digging it out of the ground and burning it produce carbon emissions.

  • To decarbonize to take carbon dioxide out of the equation we need an alternative like wind power.

  • Here in the UK renewables like wind and solar, even wave power are already providing just under  

  • half our energy needs but they don't always work  as efficiently as they could and some companies  

  • are using artificial intelligence to try and change that. Here to explain how is former Crowd  

  • scientist Graihagh Jackson.

  • Hi Graihagh.

  • Hi Marnie.

  • The reason we've asked you to come back is because you've now got your own show, also on the BBC World  Service about climate change.

  • What's that called?

  • The Climate Question. We basically look at why we find it so hard to save our planet.

  • Like what's holding us back from taking action.

  • So you're the perfect person to talk to about a project linking renewable energies to smart  tech.

  • I mean there are really high hopes for renewable energy as one of the big solutions to climate change but there are some problems.

  • There's always a problem isn't there. And it's something experts call intermittency. I'm gonna let Enass Abo-Hamed explain that.

  • She's an award-winning scientist originally from Palestine but she now lives in the UK where she co-founded a company called

  • H2 Go Power.

  • Renewable energy is intermittent by  its nature because we're dependent and relying on

  • the weather. When the sun shines and when the wind blows. And these by nature are not  

  • 24 hour 7 reliable constant.

  • And that means that  demand doesn't always meet supply of renewables?

  • It can mean that we get blackouts but on the other hand it means that when the sun is up and we were producing all that

  • power or when the wind is blowing and we're producing power we might not be able to use that energy -

  • there's no demand for it. And so it's wasted.

  • That is absolutely true. Demand varies a lot and it varies with all the changes that we have.

  • When we've had Covid hitting us our behaviour changed which meant our demand for electricity changed

  • and the grids are not designed to be extremely flexible. But if we had a source of reliable storage that could bridge this gap between supply  and demand.

  • We could achieve better results.

  • Her team have developed this artificially intelligent algorithm that predicts when there's surplus renewable energy

  • and when there's high demand. So when there's excess it stores the electricity as hydrogen and when there's

  • high demand it converts the hydrogen back into electricity. That sounds pretty simple, what makes it smart  though?

  • Well I've made it sound really simple but actually grids are these really big complicated beasts and if you throw in the unpredictability of  

  • weather and then the fluctuating demand for power there's actually quite a lot of data to process  

  • and then act upon, make a decision. So what the artificially intelligent algorithm is doing is  

  • essentially calling the shots, working out when it's best to do what.

  • And Enass has been trialling this in Orkney this is a little island off the  north coast of Scotland, a country close to  

  • your heart Marnie I believe?

  • Yes a place of weather some of it quite bad.

  • Orkney is a really interesting test bed because you're talking about a remote island,

  • not a very good connection and the weather conditions there that you have  a lot of variability.

  • You could have like a week off a lot of wind and then a week of nothing so  basically you're talking about prediction software

  • that allows you to know when the wind turbine is going to generate a lot of wind or not based on the weather

  • and then the ability to take that data  process it and predict well in advance what is the best point to instruct

  • the system to store and then convert it back to the grid.

  • And you mentioned that it's stored as hydrogen, why hydrogen and why  not just use batteries?

  • The thing about batteries is they don't hold charge for a long period of time normally people talk about one to four hours.

  • The 12 plus r1s are just not really that cost effective at the scale we need them to store  

  • all this surplus renewable energy and this is where it makes sense to convert that electricity  

  • into hydrogen because you can store it for much much longer and then convert it back whenever  

  • you need it.

  • And how do you do that, how do you make the hydrogen?

  • Split water molecules, H2o, by passing an electric current through that and in this case you create that electric current

  • with wind so when you want electricity at the other end you simply recombine the oxygen and the hydrogen

  • to create water and importantly electricity.

  • Are there other ways people are using computer technology to make wind farms more efficient?

  • Let's just look at the wind farm for a moment. Before they're even built engineers are using these really sophisticated

  • computer models to make sure that even the blades are the best shape they possibly can

  • to harness as much wind as possible. And then if there's going to be more than one turbine software

  • can make sure that they're placed in the perfect position so one turbine doesn't block another one's bit of wind.

  • And then even when they're built some engineers use something called a digital twin. This is really  

  • interesting actually this is where lots of sensors are attached to the wind turbine so it can be  

  • modeled on a computer in real time and then using machine learning you can then simulate  

  • what's happening to the wind turbine in specific weather conditions and this is important because  

  • it means they can make sure they're performing at their best. So basically computer modelling,  

  • smart tech can be involved at every single step of the process here.

  • Thank you Graihagh. In return for helping Crowdscience I've helped Graihagh with an episode of

  • The Climate Question where together we looked in detail at the promise of green hydrogen.

  • Find it wherever you get your podcasts. In summary I've learned that smart grids don't just transport power

  • from a source to a plug socket, they're two-way using lots of data to know when conditions

  • require more electricity and when to save it up for later. Smart grids allow more localised storage

  • which means more flexibility which we'll need to respond to increasingly noticeable extreme weather events.

  • And according to Srinivasan Keshev if all of the electric gadgets in our home  connect to these smart grids a computer can start  

  • the washing machine when the electricity is cheapest without us having to lift a finger.  

  • It's not going to be possible for humans to deal with the variability and demand. They may not even  

  • be home to deal with this so many people have put together what they call a home energy controller  

  • and that home energy controller has the role of forecasting your occupancy, forecasting the demand  

  • and forecasting the price that they expect to see based on observations of weather, or past history  

  • or using AI techniques, or talking to other home energy controllers and then saying we're going to  

  • take these actions and our goal is to keep you comfortable but also reduce your energy demand.  

  • And do you think in the future as part of this people are going to have batteries in their home  

  • that sort of store up energy so that the grid is much more of a two-way system -

  • it's not just us taking electricity from the system?

  • There have been a bunch of technological changes which have been super positive.

  • One of them is the rise of solar  and of wind and the holy grail in some sense is for people to install their own solar panel

  • on the rooftop and put in a storage battery in the garage and they essentially meet

  • all of the energy needs themselves. With electric cars coming in there's actually a possibility

  • that we don't need to buy storage, we can just use our cars.

  • So I have an electric car at home and it has 50 kilowatt hours of storage. It's a lot of storage

  • enough for about a week of my electricity consumption so all I need  to do would be to store the sunlight by day

  • and then at night just have my car parked by my house.

  • This is something that is almost there, we need perhaps a few more years but I fully envisioned that in  the five years

  • from now when you buy an electric car it'll be a bi-directional electric car and so you'll

  • put your solar panels on the roof and so your car is being run on sunshine from your home and at night your car runs your lights.

  • This is Crowdscience from the BBC World Service and this week we're looking at some of the clever  

  • ways in which smart tech can help us save and store energy and avoid warming the planet.

  • We've heard how renewables that help us reduce our reliance on fossil fuels like coal and gas can  

  • be made more effective by digital systems. Whether that's by using artificial intelligence to predict  

  • when the wind will blow harder or by allowing us to program our homes to be clever about when we  

  • use that electricity. In the developing world where national grids may be smaller and less complicated  

  • than the existing ones we have here it may be even easier to introduce this type of smart technology.  

  • Of course electric cars are expensive and while Keshav's dream of vehicle-powered homes might  

  • only be achievable for the most wealthy people on the planet it is still an inspiring idea.  

  • But energy consumption in our homes isfraction of what we need to power the office  

  • blocks where many of us work or at least where we used to work before the pandemic.  

  • I've come to the brand new offices of the engineering firm Arcadis  in the heart of London's financial district  

  • and it quickly becomes apparent that this no ordinary office block.

  • Welcome your host Matthew has been notified that you're here and  will meet you shortly. Take a seat.

  • Hello hello that's here can I get you a drink or anything?

  • This is a sumptuous space so I wouldn't be too surprised if they did have an automated cocktail  

  • bar. The whole building has a futuristic feel to it from the wall made of LED screens to the touch  

  • screen coffee hubs. There's also a lot of greenery, plants everywhere and they're not just for show.  

  • Arcadis's head of technology Matthew Martin says there's a lot more to this place than meets the eye.

  • I think of a smart building as giving you all sorts of outcomes to do with sustainability,  

  • to do with space and for sapiens so that means that the technology uses data and the sorts of  

  • insights to do something that's quite cool for you know how everything operates. Not very articulate that...

  • No no no I think it's one of those things that you might need to demonstrate in order for me to  

  • to get the gist of it. So where's the first  smart thing I'd encounter if I came in?  

  • The first thing that happened when you came through the door was that you went up in a lift  

  • that's got something called destination control and that means by knowing who you are where you're  

  • going to visit it's able to balance and optimise who gets into which lift so that it's able to  

  • firstly reduce the amount of energy consumption and help to make the lift kind of last longer  

  • because it reduces the travel times and distances that it goes by getting folks to group together.  

  • We'll go around into the canteen. So one of the the ways in which we've designed this office  

  • here is all to do with collaboration and in order to deal with a space that's like that  

  • can be quite challenging which is why you need some of the sort of smart building software in  

  • the first place to make that happen. That software is actually a massive computing system designed to  

  • process loads and loads of real-time information about how the building is being used. Everyone who  

  • works here has a smartphone which they use to book meeting rooms, control the temperature in a  

  • specific area, open a locker and even find out where their colleagues are at any given time.  

  • And dotted all over the ceiling are little  sensors that measure all sorts of different things.  

  • We've got around 8,000 sensors across the building generating 1.85 million points of data a day so  

  • that we can balance all of that sort of stuff and some of the things that we're looking for  

  • includes humidity temperature, co2, volatile organic  compounds as well as things like pm 2.5 and it's  

  • able to give us a score to reassure folks that we're providing a very healthy space for us to  

  • be in. Actually this is now going down the score because i'm breathing on it exactly  

  • because we are giving it carbon dioxide which will  mean that you see the machinery above your head  

  • will start to ramp up to give more pressure into  the space to react to what we're doing here.  

  • iI's all sounding smart so far, what else have  you got to show me?

  • We'll take you upstairs now.

  • We're in the winter garden right now and this is  where the lighting strategy you can just about see  

  • it because it's not particularly bright outside  in the lighting system that we've provided we're  

  • expecting to save about 60% from a normal system  and it works on kind of three ways so firstly  

  • the fact it runs on LEDs rather than anythingbit more traditional. The second is that from the  

  • occupancy sensors that you can see it's able  to tune on the basis of who's here and who  

  • isn't and then thirdly it does something called  daylight harvesting which means it will only top  

  • up synthetic light in addition to what the sun  isn't providing so you can just see around the  

  • edge, feel though it's a bit kind of overcast today  that it's definitely dimmer than what it is inside.

  • So the lights above us are they going to switch  off once we've disappeared?

  • Exactly they will give us a little bit of linger time to make sure it's  just not that we're being really still and focused  

  • and then they will wind down.

  • I think we've got them at the BBC they're just kind of you're working late in the evening

  • you need to kind of swing your arms about because otherwise you're sitting there in darkness.

  • Your's sound like they're done on something called passive infrared which means it has to see motion

  • of some sort whereas ours detects infrared - they can see that we've got a person that's

  • an alive blob and so that's how it looks.

  • Because the thing when you're editing late at  night is you're not moving you're you're staring  

  • at a computer screen.

  • And then it gets spooky.

  • Then it does yeah. Do you know how much energy a building normally takes to run per square meterper year for a commercial building?

  • We're looking at about 160 kilowatt hours. The challenge for  buildings going forward will be as to how they operate

  • with net zero because I'd expect that to be more at the kind of 55 mark for something that's achievable

  • to replace with renewables so  we're basically asking quite a lot from our people and the way that buildings operate

  • to be able to do it. Typically 40% of your energy comes from your heating, ventilation, air conditioning,

  • 5% from your lights and 55% from your plug load so to get to net  zero we're basically saying we'll swelter in  

  • the summers and freeze in the winters. We'll have  to buy some candles so that we can see what we're  

  • doing and we have to ask everybody to pre-charge  their devices before they come to the office

  • Which doesn't really solve the issue it just moves it elsewhere.

  • Right okay are you saying that net zero is not not feasible unless you have a huge amount of solar panels and wind turbines on the  

  • roof and things?

  • It's absolutely feasible and  I think any kind of company that isn't using something like

  • hvac analytics really needs to  open their eyes to the power of what it can do and that's something that we've baked into the

  • design of this building so collecting the data from those 8,000 plus sensors that we have

  • we're able to use some proper cloud scale intelligence to look at ways in which we can

  • reduce our energy consumption. All those things add up to what I would expect to be about a 20% saving

  • across the entire usage of electricity so it helps us to get down to that key 55 number.

  • And you said 8,000 sensors, I mean presumably those are all

  • electricity based and so isn't there a huge cost  to using a load of cloud storage and algorithms  

  • and and sensors to monitor the whole situation?

  • Very minimal and a lot of them are actually battery based. The power requirement is very low

  • and when you talk about using cloud computing yes there is definitely an energy cost to it but  by using that little bit for the sake of a server  

  • versus the 20% we get back for a whole building  that definitely adds up.

  • Net zero means adding no greenhouse gases to the atmosphere. What  that means in reality is that you balance what you  

  • put in with what you take out so at the moment  some companies claim to be net zero they still  

  • produce carbon dioxide since their buildings use  energy which might not all come from renewables  

  • then they offset that by planting trees but  Matthew argues the intelligence system he's built  

  • means that you don't have to use as  much electricity in the first place.  

  • Many new buildings have some form of renewable  energy generator on site but digital technology  

  • isn't just helpful for new buildings. Surrounding  Matthew's new office in the city of London is  

  • architecture that dates back hundreds of years and  those buildings can be retrofitted with sensors so  

  • they can also optimize the heating and lighting  according to which employees aware. Small privacy  

  • point these particular sensors aren't cameras  they just detect you as a living blob no offense  

  • and the small changes they make in response  to how we humans use a building all add up to  

  • meaningful efficiency savings. I've said in this  show we'd look at efficiency in three sectors  

  • we've looked at the energy sector and at buildings  and finally we're focusing on something we've been  

  • doing for thousands of years farming. Essential  for feeding and clothing the almost eight billion  

  • people on this planet but agriculture isbig contributor to greenhouse gas emissions.  

  • From the methane belching livestock to the gases produced from using fertiliser  

  • which are also often made from fossil fuels like  natural gas from deforestation to biomass burning.  

  • So I asked Keshav is farming a place where data  can help?

  • If you are able to measure the soil properties on each part of your farm in a fine grained way that means every square meter perhaps  

  • then you wouldn't use the same amount of  fertilizer everywhere. You know you use a  

  • fertilizer in those parts of the farm you need  it and less otherwise. I mean the farmers have  

  • incentive from the perspective of their costs to do  this.

  • What he's talking about is precision farming. It's becoming more and more common in the west  where it's saving large farms a lot of money.  

  • Not only are they using less water, fertilizer and pesticides but the huge amount of information  

  • generated by satellites and soil sensors can  help farmers identify the best time to plant  

  • and harvest crops. It means less wastage and  oh look there's a theme developing here that  

  • reduces their overall carbon footprint. The World  Economic Forum reckons that if these techniques  

  • were employed by just a quarter of farms globally  greenhouse gas emissions could be reduced by 10%  

  • in this sector over the next decade. So let's look  at India where agriculture is big business and to  

  • find out more i spoke to crowd science  correspondent and determined city girl  

  • Chhavi Sachdev.

  • 70% of India lives outside the  cities, unlike me and most of those folks are involved in agriculture and growing food for us  and a lot of the world. It's what their parents  

  • and grandparents and great great grandparents  have always done and that's how their knowledge  

  • has also been transferred. For instance I spoke to Manju Badekar. Her family  

  • owns a quarter of an acre of land about six hours away from Mumbai in Kashegaon village.

  • I have 10 guntas or a quarter of an acre of landWe grow sugarcane and peanuts we also have brown  

  • gram or chickpeas. We sometimes grow wheat but  no rice. It works the way it's always worked  

  • so for instance every year in this season which is  the monsoon season we know we should grow peanuts.  

  • Then after that sugarcane then in the festival  of diwali or Dussehra we go back to peanuts.  

  • How do we check whether to add fertilizers or when  to water? We can see the insects. They're generally  

  • white and we can see when we should water the  crops or not. My in-laws do this and they taught us.  

  • We go by the time and season around here, it's  always been like that.

  • So it's not a sector that I can immediately see there being scope fordigital innovation but then again India has a  

  • lot of smartphones.

  • Yes but there is lots of scopeIt's not like it's not possible and that's what we're going to get into and to understand

  • a little more i spoke to Dr Madhurama Sethi, the Indian Council of Agricultural Research.

  • We must understand that 80% of farm holdings

  • in India are fragmented and belong to marginal and  small farmers and these farmers have been farming  

  • their small land holdings for centuries. They have  been familiar with tilling cropping harvesting and  

  • understand their water and soil requirements very  well. In recent times even though their reach to  

  • information has increased with the use of mobile  phones and they have access to weather reports on  

  • soil health including sowing advice, that's all  they will look at. They will not read subsequent  

  • messages sent to them about irrigation  practices or what they need to do for  

  • water application etc because functional literacy  is low. Besides that if you send them precision  

  • farming data by way of maps etc they are unable  to understand them or interpret them in any way.  

  • This is the biggest factor holding back adoption  of precision farming.

  • I'm getting this picture of there's traditional farming where people just  do what they've always done and then there are  

  • these academics and scientists who are saying look  there are loads of really cool bits of tech that  

  • can make you do it better is that what precision  farming is?

  • So precision farming as opposed to traditional farming is when you're using really targeted data and information to make decisions  

  • about farming. In India you know technology is  what it is and there are lots of companies that  

  • have stepped up because they realise it's a big  market gap and they're using digital technology  

  • and data to try and improve this situation. One of  them is a company called Cropin which has an app  

  • in particular called Smart Farm that aims to be  a complete farm management system. So what they do  

  • is they use AI and machine learning for everything  from geotagging the land to sending weather alerts  

  • and prompts and monitoring the process of growing  the crops. So if a farmer needs certification it's  

  • all logged and this is the CTO Rajesh Jalan.

  • Through our application the farmers typically either the farmer or someone whom we call as field  officer

  • captures all the details about that farm starting with the geolocation, the soil quality.

  • Based on that an agronomist can really get data on each and every part of the land and how to

  • deal them differently. For example the agronomist could say that in Gujarat this is the time to

  • sow and at the same time it can say Himachal wait for couple of weeks.

  • Because our product  will enable them to see the weather conditions are different in both of them.

  • Chhavi, I'm really interested to know more about how this app links up to farmers like Manju who we just heard from

  • at the beginning who doesn't even have a smartphone?

  • Yeah that's definitely a challenge and Crop In knows that literacy and access to smartphones and  

  • data is the issue and they've put in a secondary  system where field officers are trained in the  

  • community to spread the alerts like a human alert  system.

  • If precision farming were to expand what kind of effect would this app have on climate  change or emissions from farming in India?

  • Well according to Crop In the results are astoundingSo Jalen says they have 16 million digitised acres  

  • with 2 million Indian farmers. Already the farmers  are reaping 30 to 40 percent more yield in a  

  • sustainable way and so working with data about  soil about wind and weather patterns means they're  

  • using less water less pesticides and this also  means reduced emissions from overuse of chemicals.  

  • 30 to 40% that's quite impressive and I'm just  wondering is Crop In the only company doing  

  • this or is this the sort of thing that's becoming  really widespread in India?

  • Oh it's definitely growing. So this kind of smart technology in the  sector is called agrotech. I found all sorts of  

  • other examples when I was doing my research from  mobile phone technology to run irrigation systems  

  • or a robot based seed sowing program  that's connected to the internet of things.  

  • Yhe only thing to remember is that all of this  relies on farmers having access to smartphones,  

  • data networks and of course the ability to read.

  • It's not just illiteracy that's the problem here. I can see how someone like Manju the farmer that  Chhavi spoke with might not be convinced that an  

  • app's going to do a better job of telling her when  to add pesticides than just using her own eyes to  

  • check for bugs on leaves. And with just a quarter  of an acre to farm it may not seem worth it to  

  • invest in the tech. Then you've got to consider  that smartphones require data networks which are  

  • notoriously patchy the more remote you get so  is this kind of upgrade to traditional farming  

  • really just a rich country thing? Well Keshav says that the technology doesn't actually need  

  • to be that expensive or complicated to have a big  impact.

  • Being a farmer in a developing region is one of the most risky businesses you could ever

  • get into. Choosing what crop varieties to plant, when to plant it, how much to water it,

  • when should you harvest it, what to do when you have pests coming in, what kind of fertilizer inputs to use,

  • when to put it in. I mean really there's thousands of things you need to take into account and if you  mess up

  • on any one of them you lose your crop. The main thing we can do to help them is to improve the state of their knowledge even as something  

  • as simple as being able to listen to a radio  program that says okay farmers in your region have  

  • experienced these kinds of conditions and this  is what they're doing is actually very valuable  

  • feedback to them. Another technology that's very  useful and it's getting cheaper all the time is  

  • just regular mobile phones where you can call up  a toll-free number and listen to targeted feedback  

  • from agricultural experts about situations in  that neighbourhood.

  • Maybe using words like digital and tech are misleading here ultimately this comes down to gathering information that helps people  

  • make better decisions. That information can be  fed into sophisticated algorithms attached to an  

  • app or it can be stored in a database that's  sent out on local radio or via text messages.  

  • The world wide web is only 32 years old but analog  life already has an impressive digital carapace a  

  • sort of technological second skin we're monitoring  and connecting life on earth as never before  

  • and if you think all that data might be creatingcarbon footprint of its own well good news because  

  • the total amount of energy spent on powering all  of the digital technology in the world that's all  

  • of the computers mobile phones cell towers data  centers only comes to about 2% of total  

  • emissions. How do we know this? Well it's thanks to  data of course. In connecting everything digitally  

  • with all this extra information, privacy and  security is vital. What happens if digital networks  

  • get hacked or data falls into the wrong hands? We didn't have time to get into cyber security  

  • but it is worth at least a whole episode on its  own and crowd science will come back to it later.  

  • As the latest IPCC report lays out a red warning  for humanity I take some comfort in all the people  

  • out there using this information to be cleverermore efficient about the lives we lead.

  • We've shown it can make a difference to the buildings  in which we live and work the electricity grids  

  • that power them or the farming that feeds the  planet all have scope to do the same job cleaner,  

  • greener and therefore better. Call me an optimist  but I find that encouraging.

  • Perhaps unsurprisingly so does Keshav.

  • Each of these underlying systems  is a traditional system. These are actually not high-tech systems.

  • By adding to them the ability  to analyse data, to do this what-if analysis, what if you did this, what would happen,

  • these oil systems get transformed. So these kinds of digital technologies which are getting unleashed upon the  world when used the right way.

  • But the appropriate policies and regulations I think will make it  possible for us to move to a world where we're  

  • not going to be in a situation as absolutely  terrible climate change you know. We are heading  

  • with the business as usual scenario to some pretty  terrible consequences and luckily we do have at  

  • our disposal some very very powerful tools. And now  it's a matter of getting the tools and the tool  

  • builders and the policy makers to get together  and use these tools for the benefit of humanity.

  • Thanks for listening to Crowdscience from the BBC World Service.

  • Today's question was from me, Saugat Bolakhe in Nepal, the presenter was Marnie Chesterton and the producer was Marik Peters.

  • If you want to write to them with your own question  you can email crowd science at bbc dot co dot uk.

Hello Crowd Science, it's Saugat Bolakhe here from  Nepal. My question actually revolves around the  

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氣候變遷(How can smart tech tackle climate change? CrowdScience - BBC World Service)

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    王杰 發佈於 2022 年 05 月 22 日
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