{"id":7,"date":"2025-12-29T00:44:47","date_gmt":"2025-12-29T00:44:47","guid":{"rendered":"https:\/\/vitallab.growthrowstory.com\/?p=7"},"modified":"2025-12-29T00:44:47","modified_gmt":"2025-12-29T00:44:47","slug":"deep-learning-va-phan-tich-du-lieu-bi-quyet-dua-trang-trai-heo-viet-nam-vao-ky-nguyen-ai-cung-trackfarm","status":"publish","type":"post","link":"https:\/\/vitallab.growthrowstory.com\/?p=7","title":{"rendered":"Deep Learning v\u00e0 Ph\u00e2n T\u00edch D\u1eef Li\u1ec7u: B\u00ed Quy\u1ebft \u0110\u01b0a Trang Tr\u1ea1i Heo Vi\u1ec7t Nam V\u00e0o K\u1ef7 Nguy\u00ean AI C\u00f9ng TrackFarm"},"content":{"rendered":"

Th\u1ebf gi\u1edbi \u0111ang thay \u0111\u1ed5i, v\u00e0 ng\u00e0nh ch\u0103n nu\u00f4i heo c\u0169ng kh\u00f4ng ngo\u1ea1i l\u1ec7. T\u1eeb nh\u1eefng ph\u01b0\u01a1ng ph\u00e1p truy\u1ec1n th\u1ed1ng d\u1ef1a v\u00e0o kinh nghi\u1ec7m v\u00e0 quan s\u00e1t th\u1ee7 c\u00f4ng, ch\u00fang ta \u0111ang b\u01b0\u1edbc v\u00e0o k\u1ef7 nguy\u00ean c\u1ee7a Trang tr\u1ea1i Th\u00f4ng minh (Smart Farm)<\/strong>, n\u01a1i c\u00f4ng ngh\u1ec7 Tr\u00ed tu\u1ec7 Nh\u00e2n t\u1ea1o (AI) v\u00e0 H\u1ecdc s\u00e2u (Deep Learning) \u0111\u00f3ng vai tr\u00f2 trung t\u00e2m. Trong b\u1ed1i c\u1ea3nh \u0111\u00f3, TrackFarm n\u1ed5i l\u00ean nh\u01b0 m\u1ed9t ng\u01b0\u1eddi ti\u00ean phong, mang \u0111\u1ebfn gi\u1ea3i ph\u00e1p qu\u1ea3n l\u00fd trang tr\u1ea1i heo th\u00f4ng minh, hi\u1ec7u qu\u1ea3 v\u00e0 b\u1ec1n v\u1eefng, \u0111\u1eb7c bi\u1ec7t t\u1eadp trung v\u00e0o vi\u1ec7c \u1ee9ng d\u1ee5ng s\u00e2u r\u1ed9ng c\u00e1c m\u00f4 h\u00ecnh d\u1eef li\u1ec7u ph\u1ee9c t\u1ea1p.<\/p>\n

I. TrackFarm: Kh\u1edfi Ngu\u1ed3n T\u1eeb D\u1eef Li\u1ec7u v\u00e0 T\u1ea7m Nh\u00ecn<\/h2>\n

TrackFarm, \u0111\u01b0\u1ee3c th\u00e0nh l\u1eadp v\u00e0o n\u0103m 2021, kh\u00f4ng ch\u1ec9 l\u00e0 m\u1ed9t c\u00f4ng ty c\u00f4ng ngh\u1ec7 m\u00e0 c\u00f2n l\u00e0 m\u1ed9t \u0111\u1ed1i t\u00e1c chi\u1ebfn l\u01b0\u1ee3c cho c\u00e1c nh\u00e0 ch\u0103n nu\u00f4i. N\u1ec1n t\u1ea3ng c\u1ee7a TrackFarm l\u00e0 s\u1ef1 k\u1ebft h\u1ee3p gi\u1eefa c\u00f4ng ngh\u1ec7 Deep Learning ti\u00ean ti\u1ebfn<\/strong> v\u00e0 m\u1ed9t kho d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3, nh\u1eb1m gi\u1ea3i quy\u1ebft nh\u1eefng th\u00e1ch th\u1ee9c l\u1edbn nh\u1ea5t trong ng\u00e0nh: d\u1ecbch b\u1ec7nh, qu\u1ea3n l\u00fd c\u00e1 th\u1ec3 v\u00e0 t\u1ed1i \u01b0u h\u00f3a n\u0103ng su\u1ea5t.<\/p>\n

A. Th\u00e1ch Th\u1ee9c Truy\u1ec1n Th\u1ed1ng v\u00e0 Nhu C\u1ea7u \u0110\u1ed5i M\u1edbi<\/h3>\n

Trong ch\u0103n nu\u00f4i heo, vi\u1ec7c ph\u00e1t hi\u1ec7n s\u1edbm b\u1ec7nh t\u1eadt l\u00e0 y\u1ebfu t\u1ed1 s\u1ed1ng c\u00f2n. M\u1ed9t con heo b\u1ec7nh c\u00f3 th\u1ec3 l\u00e2y lan nhanh ch\u00f3ng, g\u00e2y thi\u1ec7t h\u1ea1i kinh t\u1ebf nghi\u00eam tr\u1ecdng. Ph\u01b0\u01a1ng ph\u00e1p truy\u1ec1n th\u1ed1ng d\u1ef1a v\u00e0o vi\u1ec7c quan s\u00e1t c\u1ee7a nh\u00e2n vi\u00ean, v\u1ed1n d\u1ec5 b\u1ecb sai s\u00f3t, ch\u1eadm tr\u1ec5 v\u00e0 kh\u00f4ng th\u1ec3 theo d\u00f5i 24\/7. T\u01b0\u01a1ng t\u1ef1, vi\u1ec7c qu\u1ea3n l\u00fd n\u0103ng su\u1ea5t th\u01b0\u1eddng ch\u1ec9 d\u1eebng l\u1ea1i \u1edf m\u1ee9c th\u1ed1ng k\u00ea t\u1ed5ng th\u1ec3, thi\u1ebfu \u0111i c\u00e1i nh\u00ecn chi ti\u1ebft v\u1ec1 hi\u1ec7u su\u1ea5t c\u1ee7a t\u1eebng c\u00e1 th\u1ec3 heo.<\/p>\n

TrackFarm ra \u0111\u1eddi \u0111\u1ec3 l\u1ea5p \u0111\u1ea7y kho\u1ea3ng tr\u1ed1ng n\u00e0y, chuy\u1ec3n \u0111\u1ed5i trang tr\u1ea1i t\u1eeb m\u1ed9t m\u00f4i tr\u01b0\u1eddng ph\u1ea3n \u1ee9ng (reactive) sang m\u1ed9t h\u1ec7 th\u1ed1ng d\u1ef1 \u0111o\u00e1n v\u00e0 ch\u1ee7 \u0111\u1ed9ng (predictive and proactive).<\/p>\n

II. Tr\u00e1i Tim C\u00f4ng Ngh\u1ec7: Deep Learning v\u00e0 H\u1ec7 Th\u1ed1ng Camera AI<\/h2>\n

\u0110i\u1ec3m kh\u00e1c bi\u1ec7t c\u1ed1t l\u00f5i c\u1ee7a TrackFarm n\u1eb1m \u1edf vi\u1ec7c \u1ee9ng d\u1ee5ng Deep Learning<\/strong>\u2014m\u1ed9t nh\u00e1nh c\u1ee7a AI\u2014\u0111\u1ec3 ph\u00e2n t\u00edch d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh v\u00e0 h\u00e0nh vi c\u1ee7a heo. \u0110\u00e2y kh\u00f4ng ch\u1ec9 l\u00e0 vi\u1ec7c l\u1eafp \u0111\u1eb7t camera; \u0111\u00e2y l\u00e0 vi\u1ec7c x\u00e2y d\u1ef1ng m\u1ed9t “b\u1ed9 n\u00e3o” k\u1ef9 thu\u1eadt s\u1ed1 c\u00f3 kh\u1ea3 n\u0103ng “nh\u00ecn” v\u00e0 “hi\u1ec3u” t\u1eebng con heo.<\/p>\n

A. Ph\u00e1t Hi\u1ec7n B\u1ec7nh S\u1edbm: Khi Camera Tr\u1edf Th\u00e0nh B\u00e1c S\u0129<\/h3>\n

H\u1ec7 th\u1ed1ng camera AI c\u1ee7a TrackFarm li\u00ean t\u1ee5c gi\u00e1m s\u00e1t chuy\u1ec3n \u0111\u1ed9ng, t\u01b0 th\u1ebf, v\u00e0 c\u00e1c h\u00e0nh vi b\u1ea5t th\u01b0\u1eddng c\u1ee7a heo. \u0110\u00e2y l\u00e0 n\u01a1i Deep Learning ph\u00e1t huy s\u1ee9c m\u1ea1nh t\u1ed1i \u0111a.<\/p>\n

    \n
  1. Thu th\u1eadp D\u1eef li\u1ec7u H\u00e0nh vi:<\/strong> C\u00e1c m\u00f4 h\u00ecnh Deep Learning \u0111\u01b0\u1ee3c hu\u1ea5n luy\u1ec7n tr\u00ean m\u1ed9t t\u1eadp d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3, bao g\u1ed3m h\u01a1n 7.800 m\u00f4 h\u00ecnh d\u1eef li\u1ec7u heo<\/strong> (Object Management). D\u1eef li\u1ec7u n\u00e0y bao g\u1ed3m c\u00e1c tr\u1ea1ng th\u00e1i b\u00ecnh th\u01b0\u1eddng (\u0103n, ng\u1ee7, di chuy\u1ec3n) v\u00e0 c\u00e1c d\u1ea5u hi\u1ec7u s\u1edbm c\u1ee7a b\u1ec7nh (ho, run r\u1ea9y, n\u1eb1m l\u00ec, thay \u0111\u1ed5i t\u01b0 th\u1ebf n\u1eb1m).<\/li>\n
  2. Ph\u00e2n t\u00edch Th\u1eddi gian Th\u1ef1c:<\/strong> Thu\u1eadt to\u00e1n Deep Learning x\u1eed l\u00fd h\u00e0ng tri\u1ec7u khung h\u00ecnh m\u1ed7i ng\u00e0y. N\u00f3 kh\u00f4ng ch\u1ec9 nh\u1eadn di\u1ec7n con heo (Object Management) m\u00e0 c\u00f2n ph\u00e2n t\u00edch c\u00e1c thay \u0111\u1ed5i tinh vi trong h\u00e0nh vi c\u1ee7a ch\u00fang. V\u00ed d\u1ee5, m\u1ed9t con heo c\u00f3 th\u1ec3 b\u1eaft \u0111\u1ea7u di chuy\u1ec3n ch\u1eadm h\u01a1n 10% so v\u1edbi m\u1ee9c trung b\u00ecnh c\u1ee7a nh\u00f3m, ho\u1eb7c th\u1eddi gian n\u1eb1m ngh\u1ec9 c\u1ee7a n\u00f3 t\u0103ng l\u00ean \u0111\u00e1ng k\u1ec3. \u0110\u00e2y l\u00e0 nh\u1eefng d\u1ea5u hi\u1ec7u m\u00e0 m\u1eaft ng\u01b0\u1eddi kh\u00f3 c\u00f3 th\u1ec3 nh\u1eadn ra k\u1ecbp th\u1eddi.<\/li>\n
  3. D\u1ef1 \u0111o\u00e1n B\u1ec7nh (Disease Prediction):<\/strong> D\u1ef1a tr\u00ean s\u1ef1 thay \u0111\u1ed5i h\u00e0nh vi n\u00e0y, h\u1ec7 th\u1ed1ng s\u1ebd \u0111\u01b0a ra c\u1ea3nh b\u00e1o s\u1edbm. \u0110\u00e2y l\u00e0 m\u1ed9t b\u01b0\u1edbc ti\u1ebfn v\u01b0\u1ee3t b\u1eadc so v\u1edbi vi\u1ec7c ch\u1ea9n \u0111o\u00e1n sau khi tri\u1ec7u ch\u1ee9ng \u0111\u00e3 r\u00f5 r\u00e0ng. Kh\u1ea3 n\u0103ng d\u1ef1 \u0111o\u00e1n n\u00e0y gi\u00fap ng\u01b0\u1eddi ch\u0103n nu\u00f4i c\u00e1ch ly v\u00e0 \u0111i\u1ec1u tr\u1ecb k\u1ecbp th\u1eddi, ng\u0103n ch\u1eb7n d\u1ecbch b\u1ec7nh l\u00e2y lan.<\/li>\n<\/ol>\n
    \n

    “Deep Learning cho ph\u00e9p ch\u00fang t\u00f4i nh\u00ecn th\u1ea5y nh\u1eefng g\u00ec v\u00f4 h\u00ecnh. N\u00f3 bi\u1ebfn camera gi\u00e1m s\u00e1t th\u00e0nh m\u1ed9t c\u00f4ng c\u1ee5 ch\u1ea9n \u0111o\u00e1n y t\u1ebf, ho\u1ea1t \u0111\u1ed9ng kh\u00f4ng m\u1ec7t m\u1ecfi 24 gi\u1edd m\u1ed9t ng\u00e0y.”<\/p>\n<\/blockquote>\n

    \"Giao<\/p>\n

    B. Qu\u1ea3n L\u00fd C\u00e1 Th\u1ec3 (Object Management) v\u00e0 C\u00e1 Nh\u00e2n H\u00f3a Ch\u0103m S\u00f3c<\/h3>\n

    V\u1edbi h\u01a1n 7.800 m\u00f4 h\u00ecnh d\u1eef li\u1ec7u, TrackFarm c\u00f3 kh\u1ea3 n\u0103ng theo d\u00f5i v\u00e0 nh\u1eadn di\u1ec7n t\u1eebng c\u00e1 th\u1ec3 heo trong chu\u1ed3ng. \u0110i\u1ec1u n\u00e0y m\u1edf ra m\u1ed9t k\u1ef7 nguy\u00ean m\u1edbi c\u1ee7a vi\u1ec7c ch\u0103m s\u00f3c c\u00e1 nh\u00e2n h\u00f3a.<\/p>\n

      \n
    • Nh\u1eadn di\u1ec7n v\u00e0 Theo d\u00f5i:<\/strong> H\u1ec7 th\u1ed1ng Deep Learning g\u00e1n m\u1ed9t “d\u1ea5u v\u00e2n tay” k\u1ef9 thu\u1eadt s\u1ed1 cho m\u1ed7i con heo, cho ph\u00e9p theo d\u00f5i l\u1ecbch s\u1eed s\u1ee9c kh\u1ecfe, t\u1ed1c \u0111\u1ed9 t\u0103ng tr\u01b0\u1edfng, v\u00e0 hi\u1ec7u su\u1ea5t \u0103n u\u1ed1ng c\u1ee7a ri\u00eang n\u00f3.<\/li>\n
    • Ph\u00e2n t\u00edch Nh\u00f3m:<\/strong> N\u00f3 c\u0169ng ph\u00e2n t\u00edch s\u1ef1 t\u01b0\u01a1ng t\u00e1c gi\u1eefa c\u00e1c con heo, gi\u00fap ph\u00e1t hi\u1ec7n c\u00e1c h\u00e0nh vi g\u00e2y h\u1ea5n ho\u1eb7c b\u1ecb c\u00f4 l\u1eadp, v\u1ed1n c\u00f3 th\u1ec3 l\u00e0 d\u1ea5u hi\u1ec7u c\u1ee7a c\u0103ng th\u1eb3ng ho\u1eb7c b\u1ec7nh t\u1eadt.<\/li>\n
    • T\u1ed1i \u01b0u h\u00f3a Th\u1ee9c \u0103n:<\/strong> B\u1eb1ng c\u00e1ch theo d\u00f5i ch\u00ednh x\u00e1c t\u1ed1c \u0111\u1ed9 t\u0103ng tr\u01b0\u1edfng c\u1ee7a t\u1eebng con, ng\u01b0\u1eddi ch\u0103n nu\u00f4i c\u00f3 th\u1ec3 \u0111i\u1ec1u ch\u1ec9nh kh\u1ea9u ph\u1ea7n \u0103n m\u1ed9t c\u00e1ch khoa h\u1ecdc, tr\u00e1nh l\u00e3ng ph\u00ed v\u00e0 \u0111\u1ea3m b\u1ea3o heo \u0111\u1ea1t tr\u1ecdng l\u01b0\u1ee3ng t\u1ed1i \u01b0u nhanh nh\u1ea5t.<\/li>\n<\/ul>\n

      III. Ph\u00e2n T\u00edch D\u1eef Li\u1ec7u (Data Analytics) \u0110\u1ec3 T\u1ed1i \u01afu H\u00f3a N\u0103ng Su\u1ea5t<\/h2>\n

      N\u1ebfu Deep Learning l\u00e0 tr\u00e1i tim c\u1ee7a h\u1ec7 th\u1ed1ng, th\u00ec Ph\u00e2n t\u00edch D\u1eef li\u1ec7u<\/strong> ch\u00ednh l\u00e0 b\u1ed9 n\u00e3o, bi\u1ebfn d\u1eef li\u1ec7u th\u00f4 th\u00e0nh nh\u1eefng quy\u1ebft \u0111\u1ecbnh kinh doanh th\u00f4ng minh. TrackFarm kh\u00f4ng ch\u1ec9 cung c\u1ea5p d\u1eef li\u1ec7u; n\u00f3 cung c\u1ea5p th\u00f4ng tin chi ti\u1ebft c\u00f3 th\u1ec3 h\u00e0nh \u0111\u1ed9ng \u0111\u01b0\u1ee3c (actionable insights)<\/strong>.<\/p>\n

      A. C\u1ea3i Thi\u1ec7n Hi\u1ec7u Su\u1ea5t Trang Tr\u1ea1i v\u00e0 L\u1ee3i Nhu\u1eadn<\/h3>\n

      M\u1ee5c ti\u00eau cu\u1ed1i c\u00f9ng c\u1ee7a m\u1ecdi trang tr\u1ea1i l\u00e0 t\u1ed1i \u0111a h\u00f3a l\u1ee3i nhu\u1eadn. TrackFarm \u0111\u1ea1t \u0111\u01b0\u1ee3c \u0111i\u1ec1u n\u00e0y th\u00f4ng qua Qu\u1ea3n l\u00fd N\u0103ng su\u1ea5t (Productivity Management)<\/strong> d\u1ef1a tr\u00ean d\u1eef li\u1ec7u.<\/p>\n

        \n
      1. Ch\u1ec9 s\u1ed1 Hi\u1ec7u su\u1ea5t Ch\u00ednh (KPIs) T\u1ee9c th\u1eddi:<\/strong> Thay v\u00ec ch\u1edd \u0111\u1ee3i b\u00e1o c\u00e1o cu\u1ed1i th\u00e1ng, ng\u01b0\u1eddi qu\u1ea3n l\u00fd c\u00f3 th\u1ec3 xem c\u00e1c ch\u1ec9 s\u1ed1 quan tr\u1ecdng nh\u01b0 T\u1ef7 l\u1ec7 Chuy\u1ec3n \u0111\u1ed5i Th\u1ee9c \u0103n (FCR), T\u1ef7 l\u1ec7 T\u0103ng tr\u1ecdng H\u00e0ng ng\u00e0y (ADG), v\u00e0 T\u1ef7 l\u1ec7 T\u1eed vong theo th\u1eddi gian th\u1ef1c.<\/li>\n
      2. Ph\u00e2n t\u00edch Nguy\u00ean nh\u00e2n G\u1ed1c r\u1ec5:<\/strong> Khi n\u0103ng su\u1ea5t gi\u1ea3m, h\u1ec7 th\u1ed1ng ph\u00e2n t\u00edch d\u1eef li\u1ec7u l\u1ecbch s\u1eed v\u00e0 d\u1eef li\u1ec7u m\u00f4i tr\u01b0\u1eddng (nhi\u1ec7t \u0111\u1ed9, \u0111\u1ed9 \u1ea9m) \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh nguy\u00ean nh\u00e2n ch\u00ednh x\u00e1c. V\u00ed d\u1ee5, h\u1ec7 th\u1ed1ng c\u00f3 th\u1ec3 ch\u1ec9 ra r\u1eb1ng s\u1ef1 s\u1ee5t gi\u1ea3m ADG trong m\u1ed9t khu v\u1ef1c c\u1ee5 th\u1ec3 l\u00e0 do nhi\u1ec7t \u0111\u1ed9 chu\u1ed3ng nu\u00f4i v\u01b0\u1ee3t qu\u00e1 ng\u01b0\u1ee1ng t\u1ed1i \u01b0u v\u00e0o bu\u1ed5i chi\u1ec1u.<\/li>\n
      3. M\u00f4 ph\u1ecfng v\u00e0 D\u1ef1 b\u00e1o:<\/strong> S\u1eed d\u1ee5ng c\u00e1c m\u00f4 h\u00ecnh th\u1ed1ng k\u00ea ph\u1ee9c t\u1ea1p, TrackFarm c\u00f3 th\u1ec3 m\u00f4 ph\u1ecfng c\u00e1c k\u1ecbch b\u1ea3n kh\u00e1c nhau (v\u00ed d\u1ee5: t\u0103ng kh\u1ea9u ph\u1ea7n \u0103n 5%, gi\u1ea3m nhi\u1ec7t \u0111\u1ed9 1 \u0111\u1ed9 C) v\u00e0 d\u1ef1 b\u00e1o t\u00e1c \u0111\u1ed9ng c\u1ee7a ch\u00fang l\u00ean l\u1ee3i nhu\u1eadn.<\/li>\n<\/ol>\n

        \"H\u00ecnh<\/p>\n

        B. So S\u00e1nh: Gi\u00e1m S\u00e1t Truy\u1ec1n Th\u1ed1ng v\u00e0 Gi\u00e1m S\u00e1t AI TrackFarm<\/h3>\n

        \u0110\u1ec3 th\u1ea5y r\u00f5 s\u1ef1 kh\u00e1c bi\u1ec7t, h\u00e3y xem x\u00e9t c\u00e1ch ti\u1ebfp c\u1eadn c\u1ee7a hai ph\u01b0\u01a1ng ph\u00e1p \u0111\u1ed1i v\u1edbi c\u00e1c v\u1ea5n \u0111\u1ec1 c\u1ed1t l\u00f5i:<\/p>\n\n\n\n\n\n\n\n\n\n
        T\u00ednh n\u0103ng<\/th>\nPh\u01b0\u01a1ng ph\u00e1p Truy\u1ec1n th\u1ed1ng<\/th>\nPh\u01b0\u01a1ng ph\u00e1p AI TrackFarm (Deep Learning & Data Analytics)<\/th>\n<\/tr>\n<\/thead>\n
        Ph\u00e1t hi\u1ec7n B\u1ec7nh<\/strong><\/td>\nD\u1ef1a v\u00e0o quan s\u00e1t th\u1ee7 c\u00f4ng, ph\u00e1t hi\u1ec7n khi tri\u1ec7u ch\u1ee9ng r\u00f5 r\u00e0ng.<\/td>\nD\u1ef1a v\u00e0o ph\u00e2n t\u00edch h\u00e0nh vi Deep Learning, ph\u00e1t hi\u1ec7n s\u1edbm 2-3 ng\u00e0y tr\u01b0\u1edbc khi tri\u1ec7u ch\u1ee9ng l\u00e2m s\u00e0ng xu\u1ea5t hi\u1ec7n.<\/td>\n<\/tr>\n
        Qu\u1ea3n l\u00fd C\u00e1 th\u1ec3<\/strong><\/td>\n\u0110\u00e1nh d\u1ea5u tai, h\u1ed3 s\u01a1 gi\u1ea5y t\u1edd, kh\u00f3 theo d\u00f5i chi ti\u1ebft.<\/td>\nNh\u1eadn di\u1ec7n c\u00e1 th\u1ec3 b\u1eb1ng AI (7.800+ m\u00f4 h\u00ecnh), theo d\u00f5i 24\/7, h\u1ed3 s\u01a1 k\u1ef9 thu\u1eadt s\u1ed1 chi ti\u1ebft.<\/td>\n<\/tr>\n
        T\u1ed1i \u01b0u N\u0103ng su\u1ea5t<\/strong><\/td>\nTh\u1ed1ng k\u00ea t\u1ed5ng th\u1ec3, \u0111i\u1ec1u ch\u1ec9nh chung cho c\u1ea3 \u0111\u00e0n.<\/td>\nPh\u00e2n t\u00edch d\u1eef li\u1ec7u chi ti\u1ebft t\u1eebng c\u00e1 th\u1ec3, \u0111\u01b0a ra khuy\u1ebfn ngh\u1ecb c\u00e1 nh\u00e2n h\u00f3a, t\u1ed1i \u01b0u h\u00f3a FCR v\u00e0 ADG.<\/td>\n<\/tr>\n
        Th\u1eddi gian Ph\u1ea3n \u1ee9ng<\/strong><\/td>\nCh\u1eadm, ph\u1ee5 thu\u1ed9c v\u00e0o ca l\u00e0m vi\u1ec7c c\u1ee7a nh\u00e2n vi\u00ean.<\/td>\nT\u1ee9c th\u1eddi, c\u1ea3nh b\u00e1o t\u1ef1 \u0111\u1ed9ng qua \u1ee9ng d\u1ee5ng di \u0111\u1ed9ng.<\/td>\n<\/tr>\n
        \u0110\u1ed9 ch\u00ednh x\u00e1c<\/strong><\/td>\nTh\u1ea5p, d\u1ec5 b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi y\u1ebfu t\u1ed1 con ng\u01b0\u1eddi.<\/td>\nCao, d\u1ef1a tr\u00ean thu\u1eadt to\u00e1n \u0111\u00e3 \u0111\u01b0\u1ee3c ki\u1ec3m ch\u1ee9ng v\u00e0 d\u1eef li\u1ec7u l\u1edbn.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        B\u1ea3ng so s\u00e1nh n\u00e0y cho th\u1ea5y r\u00f5 r\u00e0ng s\u1ef1 chuy\u1ec3n \u0111\u1ed5i t\u1eeb qu\u1ea3n l\u00fd d\u1ef1a tr\u00ean c\u1ea3m t\u00ednh sang qu\u1ea3n l\u00fd d\u1ef1a tr\u00ean d\u1eef li\u1ec7u ch\u00ednh x\u00e1c v\u00e0 khoa h\u1ecdc<\/strong>.<\/p>\n

        IV. TrackFarm v\u00e0 C\u01a1 H\u1ed9i T\u1ea1i Th\u1ecb Tr\u01b0\u1eddng Vi\u1ec7t Nam<\/h2>\n

        Vi\u1ec7t Nam, v\u1edbi ng\u00e0nh ch\u0103n nu\u00f4i heo \u0111ang ph\u00e1t tri\u1ec3n m\u1ea1nh m\u1ebd, l\u00e0 m\u1ed9t th\u1ecb tr\u01b0\u1eddng ti\u1ec1m n\u0103ng l\u1edbn cho c\u00e1c gi\u1ea3i ph\u00e1p c\u00f4ng ngh\u1ec7 cao nh\u01b0 TrackFarm. S\u1ef1 m\u1edf r\u1ed9ng c\u1ee7a TrackFarm \u0111\u1ebfn th\u1ecb tr\u01b0\u1eddng Vi\u1ec7t Nam, \u0111\u1eb7c bi\u1ec7t t\u1ea1i c\u00e1c khu v\u1ef1c tr\u1ecdng \u0111i\u1ec3m nh\u01b0 Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh v\u00e0 \u0110\u1ed3ng Nai<\/strong>, l\u00e0 m\u1ed9t minh ch\u1ee9ng cho t\u1ea7m nh\u00ecn to\u00e0n c\u1ea7u c\u1ee7a c\u00f4ng ty.<\/p>\n

        A. Gi\u1ea3i Quy\u1ebft V\u1ea5n \u0110\u1ec1 C\u1ee5c B\u1ed9<\/h3>\n

        C\u00e1c trang tr\u1ea1i t\u1ea1i Vi\u1ec7t Nam th\u01b0\u1eddng \u0111\u1ed1i m\u1eb7t v\u1edbi th\u00e1ch th\u1ee9c v\u1ec1 kh\u00ed h\u1eadu n\u00f3ng \u1ea9m, d\u1ec5 ph\u00e1t sinh d\u1ecbch b\u1ec7nh. Kh\u1ea3 n\u0103ng D\u1ef1 \u0111o\u00e1n B\u1ec7nh<\/strong> c\u1ee7a TrackFarm tr\u1edf n\u00ean v\u00f4 c\u00f9ng quan tr\u1ecdng trong m\u00f4i tr\u01b0\u1eddng n\u00e0y. B\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng d\u1eef li\u1ec7u \u0111\u1ecba ph\u01b0\u01a1ng v\u00e0 \u0111i\u1ec1u ch\u1ec9nh m\u00f4 h\u00ecnh Deep Learning cho ph\u00f9 h\u1ee3p v\u1edbi gi\u1ed1ng heo v\u00e0 \u0111i\u1ec1u ki\u1ec7n chu\u1ed3ng tr\u1ea1i t\u1ea1i Vi\u1ec7t Nam, TrackFarm mang l\u1ea1i m\u1ed9t gi\u1ea3i ph\u00e1p \u0111\u01b0\u1ee3c b\u1ea3n \u0111\u1ecba h\u00f3a cao.<\/p>\n

        B. H\u1ee3p T\u00e1c v\u00e0 Ph\u00e1t Tri\u1ec3n C\u1ed9ng \u0110\u1ed3ng<\/h3>\n

        TrackFarm \u0111\u00e3 v\u00e0 \u0111ang x\u00e2y d\u1ef1ng ni\u1ec1m tin th\u00f4ng qua c\u00e1c m\u1ed1i quan h\u1ec7 \u0111\u1ed1i t\u00e1c. Vi\u1ec7c h\u1ee3p t\u00e1c v\u1edbi h\u01a1n 10 trang tr\u1ea1i v\u1eeba v\u00e0 nh\u1ecf<\/strong> cho th\u1ea5y cam k\u1ebft c\u1ee7a c\u00f4ng ty kh\u00f4ng ch\u1ec9 v\u1edbi c\u00e1c t\u1eadp \u0111o\u00e0n l\u1edbn m\u00e0 c\u00f2n v\u1edbi nh\u1eefng ng\u01b0\u1eddi ch\u0103n nu\u00f4i mu\u1ed1n hi\u1ec7n \u0111\u1ea1i h\u00f3a ho\u1ea1t \u0111\u1ed9ng c\u1ee7a m\u00ecnh. S\u1ef1 h\u1ee3p t\u00e1c n\u00e0y t\u1ea1o ra m\u1ed9t v\u00f2ng l\u1eb7p ph\u1ea3n h\u1ed3i t\u00edch c\u1ef1c: d\u1eef li\u1ec7u t\u1eeb c\u00e1c trang tr\u1ea1i \u0111\u1ed1i t\u00e1c gi\u00fap c\u1ea3i thi\u1ec7n \u0111\u1ed9 ch\u00ednh x\u00e1c c\u1ee7a m\u00f4 h\u00ecnh Deep Learning, v\u00e0 ng\u01b0\u1ee3c l\u1ea1i, c\u00e1c trang tr\u1ea1i nh\u1eadn \u0111\u01b0\u1ee3c l\u1ee3i \u00edch t\u1eeb nh\u1eefng ph\u00e2n t\u00edch ng\u00e0y c\u00e0ng tinh vi.<\/p>\n

        \"H\u00ecnh<\/p>\n

        V. T\u01b0\u01a1ng Lai C\u1ee7a Ch\u0103n Nu\u00f4i Heo: Ho\u00e0n To\u00e0n T\u1ef1 \u0110\u1ed9ng v\u00e0 D\u1eef Li\u1ec7u H\u00f3a<\/h2>\n

        T\u1ea7m nh\u00ecn c\u1ee7a TrackFarm kh\u00f4ng ch\u1ec9 d\u1eebng l\u1ea1i \u1edf vi\u1ec7c gi\u00e1m s\u00e1t v\u00e0 c\u1ea3nh b\u00e1o. M\u1ee5c ti\u00eau l\u00e0 h\u01b0\u1edbng t\u1edbi m\u1ed9t h\u1ec7 th\u1ed1ng ch\u0103n nu\u00f4i heo ho\u00e0n to\u00e0n t\u1ef1 \u0111\u1ed9ng v\u00e0 \u0111\u01b0\u1ee3c d\u1eef li\u1ec7u h\u00f3a, n\u01a1i m\u1ecdi quy\u1ebft \u0111\u1ecbnh \u0111\u1ec1u \u0111\u01b0\u1ee3c h\u1ed7 tr\u1ee3 b\u1edfi AI.<\/p>\n

        A. H\u1ecdc S\u00e2u v\u00e0 S\u1ef1 T\u1ef1 C\u1ea3i Thi\u1ec7n C\u1ee7a H\u1ec7 Th\u1ed1ng<\/h3>\n

        C\u00e1c m\u00f4 h\u00ecnh Deep Learning c\u1ee7a TrackFarm kh\u00f4ng t\u0129nh. Ch\u00fang l\u00e0 c\u00e1c h\u1ec7 th\u1ed1ng h\u1ecdc t\u1eadp li\u00ean t\u1ee5c. M\u1ed7i khi m\u1ed9t c\u1ea3nh b\u00e1o b\u1ec7nh t\u1eadt \u0111\u01b0\u1ee3c x\u00e1c nh\u1eadn ho\u1eb7c m\u1ed9t chi\u1ebfn l\u01b0\u1ee3c n\u0103ng su\u1ea5t \u0111\u01b0\u1ee3c ch\u1ee9ng minh l\u00e0 th\u00e0nh c\u00f4ng, d\u1eef li\u1ec7u \u0111\u00f3 s\u1ebd \u0111\u01b0\u1ee3c \u0111\u01b0a tr\u1edf l\u1ea1i \u0111\u1ec3 hu\u1ea5n luy\u1ec7n l\u1ea1i m\u00f4 h\u00ecnh. \u0110i\u1ec1u n\u00e0y t\u1ea1o ra m\u1ed9t chu tr\u00ecnh c\u1ea3i ti\u1ebfn li\u00ean t\u1ee5c, gi\u00fap h\u1ec7 th\u1ed1ng ng\u00e0y c\u00e0ng th\u00f4ng minh h\u01a1n theo th\u1eddi gian.<\/p>\n