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Smart Farming: Opportuni0es, Challenges and Technology Enablers Manlio Bacco 1 , A. Berton 2 , E. Ferro 1 , C. Gennaro 1 , A. Go2a 1 , S. Ma2eoli 3 , F. Paonessa 3 , M. Ruggeri 4 , G. Virone 3 , A. Zanella 3 1 Ins0tute of Informa0on Science and Technologies (ISTI) 2 Inst. of Clinical Physiology (IFC) 3 Inst. of Electronics, Computer and TelecommunicaKon Engineering (IEIIT) 4 Inst. of Agricultural MechanizaKon, EarthMoving Machinery and OffRoad Vehicles (IMAMOTER) Na0onal Research Council (CNR), Italy [email protected] Wireless Networks Laboratory, ISTI CNR – NaKonal Research Council, Pisa

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Page 1: Smart&Farming:&Opportuni0es,& …tuscany2018.iot.ieee.org/files/2018/05/IEEE-IoT-2018-May... · 2018-05-16 · Smart&Farming:&Opportuni0es,& ChallengesandTechnologyEnablers Manlio&Bacco1,

Smart  Farming:  Opportuni0es,  Challenges  and  Technology  Enablers  

Manlio  Bacco1,  A.  Berton2,  E.  Ferro1,  C.  Gennaro1,  A.  Go2a1,    S.  Ma2eoli3,  F.  Paonessa3,  M.  Ruggeri4,  G.  Virone3,  A.  Zanella3  

 1  Ins0tute  of  Informa0on  Science  and  Technologies  (ISTI)  

2  Inst.  of  Clinical  Physiology  (IFC)  3  Inst.  of  Electronics,  Computer  and  TelecommunicaKon  Engineering  (IEIIT)  

4  Inst.  of  Agricultural  MechanizaKon,  Earth-­‐Moving  Machinery  and  Off-­‐Road  Vehicles  (IMAMOTER)  Na0onal  Research  Council  (CNR),  Italy  

 [email protected]  W

ireless  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

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Outline  

•  Internet  of  Things  for  agricultural  applicaKons  –  relevant  use  cases  – enabling  wireless  technologies  – network  funcKonal  requirements  

•  a  quick  glance  at:  – Unmanned  Aerial  Systems  (UAS)  – Machine  Vision  and  Deep  Learning  

•  conclusions    

Wire

less  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy   2  

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M2M  /  IoT  -­‐  a  brief  digression  -­‐  

Wire

less  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

machine-­‐to-­‐machine:  •  refers  to  technologies  that  

allow  both  wireless  and  wired  systems  to  communicate  with  other  devices  of  the  same  ability  

•  no  direct  human  consumer  or  producer  

Internet  of  Things:    from  custom  communicaKon  soluKons  to  a  common  stack  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy   3  

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•  large  diversity  of  applicaKon  domains  and  of  communicaKon  requirements  

•  heterogeneity  and  fragmentaKon  of  the  connecKvity  landscape  thet  is  currently  hampering  the  full  realizaKon  of  the  IoT  vision,  by  posing  several  complex  integraKon  challenges  

 In  fact,  there  is  not  a  true  IoT  ecosystem,  but  a  plethora  of  verKcal  soluKons  that  are  not  interconnected  (as  IoT  would  suggest)  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

M2M  /  IoT  -­‐  a  brief  digression  -­‐  

IoT  is  not  a  single  technology,  but  it  is  a  technology  enabler  

4  

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M2M  /  IoT  -­‐  interoperability  and  compaKbility  -­‐  

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INTEROPERABILITY  is  the  ability  of  two  or  more  systems  to  exchange  and  use  informaKon:  the  informaKon  reaches  the  target  system  and  sKll  mean  the  same  thing  to  the  target  system  as  the  sending  system.        

COMPATIBILITY  is  the  ability  of  two  or  more  systems  to  perform  their  required  funcKons  while  sharing  the  same  environment.  The  two  systems  do  not  need  to  communicated  with  each  other,  but  simply  be  resident  on  the  same  environment.  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy   5  

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Agricultural  Electronic  FoundaKon  deeply  involved  in  precision  agriculture,  enabled  by  ISOBUS  (ISO  11783)  “Tractors  and  machinery  for  agriculture  and  forestry  -­‐  Serial  control  and  communica8ons  data  network”    Time-­‐Sensi0ve  Networking  (TSN)  capabili0es  for  industrial  automa0on  (an  addi0on  to  the  Ethernet  standard)  represent  a  further  step  forward  into  suppor0ng  high  speed  communica0ons  from/to  agricultural  machines.    The  evoluKon  of  ISOBUS  by  relying  on  TSN  features  is  based  on  the  exploitaKon  of  the  BroadR-­‐Reach  standard  (from  the  automo8ve  sector),  a  physical  layer  operaKng  full  duplex  over  one  pair  of  unshielded  twisted  pair  cables.  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

ISOBUS  (ISO  11783)  

6  

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 ISOBUS  can  be  considered  a  mature  standard,  but  the  same  cannot  be  said  for  the  standards  for  wireless  in-­‐field  communica0on  in  smart  farming  scenarios.    Several  reasons  are  behind  that:  •  the  vast  ecosystem  of  wireless  standards    •  the  vast  ecosystem  of  standards  for  automated  funcKons    •  commercial  interests  

Because  of  this,  a  number  of  wireless  standards  are  expected  to  be  included  into  ISO/TC  23/SC  4    “Tractors  and  machinery  for  agriculture  and  forestry”  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

wireless  communica0ons  

7  

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Farm  Management  Informa0on  Systems      using  the  informaKon  coming  from  various  sources  as  sensors  to  assist  farmers  in  the  decision-­‐making  process  •  soil  samples  •  sensor  data  •  aerial  devices  •  weather  informaKon  •  maps  •  …  

 Extended  FMIS  Data  Interface  (EFDI)  machine-­‐to-­‐cloud  or  cloud-­‐to-­‐cloud  standard  based  on  ISO  11783  focusing  on  protocols  for  data  transfers  using  wireless  communicaKons  by  exploiKng  ISOXML  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

background  and  relevant  use  cases  

8  

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less  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

Extensive  cul0va0ons  -­‐  long-­‐range  communicaKons  -­‐  

fixed  wing  UAV  

n-­‐rotors  UAV  

large  distances  (in  the  order  of  kms)  

clusters  of  huge  machines  working  in  parallel  •  real-­‐Kme  

communicaKons?  •  among  machines  √    •  with  the  CC  ?  

9  

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less  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

Orchards  and  vineyards  -­‐  medium  and  short-­‐range  communicaKons  -­‐  

rows  of  plants  precisely  posi0oned  for  automated  and  specialized  machines  •  large  use  of  WSNs  •  role  of  UAVs?    

n-­‐rotors  UAV  

10  

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 command  and  control  data  •  typically  small  amounts  of  data,  but  with  strict  constraints  on  real-­‐Kme  and  

on  reliability  •  is  it  sKll  so  for  large  clusters  of  cooperaKng  devices?  (speed  and  mulKple  

access)  

payload(s)-­‐generated  data    •  possibly  large  amount  of  data  with  less  stricter  constraints  •  very  high-­‐speed  communicaKons  for  large  clusters  of  cooperaKng  devices  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

ground  and  aerial  vehicles  -­‐  data  types  -­‐  

11  

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IEEE  802.15.4  (telemetry):  •  low  data-­‐rate  •  reduced  coverage    Bluetooth  4.2  /  5  (telemetry):    •  IPv6  /  6LowPAN  (IP  

addressable!)  •  reduced  coverage  

LoRA  /  LoRAWAN  (telemetry):  •  low  data-­‐rate  •  long-­‐range  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

wireless  technologies  802.11  (large  data  exchanges):  •  b/g/n/ac    •  p:  vehicular  standard  

–  max  1W  of  transmit  power!  

3G/4G/5G  (large  data  exchanges):  •  coverage?  •  economical  feasibility?  

12  

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(slow)  agricultural  machines  (in  public  roads:  ad-­‐hoc  adver0sement?)    802.11p  /  DSRC  •  carrier  sense  mulKple  access  with  collision  avoidance  medium-­‐access  scheme  •  some  challenges  when  guaranteeing  strict  reliability  levels  and  ensuring  the  

network’s  scalability  (as  the  load  increases)    LTE-­‐V  (sidelink  5G  V2X  vehicular  communica0ons)  •  improves  the  link  budget  w.r.t.  802.11p  •  redundant  transmissions  per  packet  •  mode  4  does  not  require  cellular  coverage!  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

wireless  technologies  

13  

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onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

aerial  vehicles  

high  resolu0on  details  and  on-­‐demand  imagery  •  water  stress  level  •  RVI,  NDVI,  PRI  (vegetaKon  indices)  •  weed  detecKon  •  (autonomous)  spraying  (VRT)  •  …  

14  

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onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

aerial  vehicles  by  CNR    for  smart  farming  

EFESTO  (UAV)  by  Sigma  Ingegneria,  CNR  Pisa  and  Zefiro    •  pest  control  •  imagery  (visible  spectral  bands  and/or  in  those  outside  the  visible  range)  

Security  regula0ons  for  flying  objects  are  evolving  day  by  day,  even  if  rural  areas  suffer  from  less  constraints  than  urban  areas  

15  

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IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

aerial  vehicles  by  CNR    for  smart  farming  

visible range im.

multispectral im.

thermal im.

16  

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IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

a  simple  taxonomy  for  UAV  missions  

17  

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MV-­‐based  applica0ons  for  (hyperspectral)  imagery  from  an  UAV:  •  agriculture  parameter  esKmaKon  and  retrieval  (e.g.  carotenoid,  chlorophyll,  

and  anthocyanin  content,  nitrogen  status,  water  content,  biomass  and  leaf  area  index)  

•  crop  classificaKon  and  crop/material  detecKon  •  disease  early  detecKon  and  monitoring  (e.g.  disease  due  to  bacteria  and  fungi  

or  caused  by  insect  infestaKon)  •  machinery  guidance  in  pre/post  crop  tasks  (e.g.  early  sowing,  precision  

ferKlizer  applicaKon,  precision  irrigaKon)  •  …  

MV  coupled  with  Deep  Learning  techniques  enables  intelligence  and  reconnaissance  scenarios  in  different  farming  scenarios!  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

Machine  Vision  

18  

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IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

The  role  of  5G  in    future  smart  farming  scenarios  

5G,  along  with  aerospace  soluKons  (such  as  UAVs),  may  bring  broadband  connecKvity  in  rural  areas,  providing  IoT  scenarios  with  fast  and  reliable  connec0ons  soawariza0on  •  SDN/NFV  •  network  slicing  low-­‐cost  solu0ons  •  commodity  hardware  •  on-­‐demand  deployments  

19  

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IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

a  future  scenario?  

20  

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IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy  

conclusions  •  highlighted  the  importance  of  interoperability  for  IoT  deployments  •  presented  the  wired  and  wireless  networking  soluKons  in  use  at  today  

•  highlighted  how  wireless  networking  sKll  lacks  a  standard  to  ease  interoperability  

•  discussed  different  requirements  in  long-­‐range  and  short-­‐range  agricultural  deployments  

•  role  and  requirements  for  UAV  complemented  by  MV  and  DL  •  5G  and  future  scenarios  

21  

Page 22: Smart&Farming:&Opportuni0es,& …tuscany2018.iot.ieee.org/files/2018/05/IEEE-IoT-2018-May... · 2018-05-16 · Smart&Farming:&Opportuni0es,& ChallengesandTechnologyEnablers Manlio&Bacco1,

Smart  Farming:  OpportuniKes,  Challenges  and  Technology  Enablers  

 Any  ques0ons?  

[email protected]    

Thank  you!  

Wire

less  Networks  Laboratory,  ISTI  CNR  –  NaK

onal  Research  Co

uncil,  Pisa  

IoT  VerKcal  and  Topical  Summit  for  Agriculture,  08-­‐09/05/2018  Italy   22