This content originally appeared on DEV Community and was authored by 🇺🇦Timothy Spann🇺🇦

FLiP-Py-Pi-GasThermal

Source: https://github.com/tspannhw/FLiP-Py-Pi-GasThermal

tags: Apache Pulsar, Python, Raspberry Pi, Gas Sensor + Thermal Camera Sensors, Apache Flink, Trino/Presto SQL

Sensors

Pimoroni BreakoutGarden: SGP30
- Sensiron SGP30 TVOC and eCO2 sensor (datasheet)
- TVOC sensing from 0-60,000 ppb (parts per billion)
- CO2 sensing from 400 to 60,000 ppm (parts per million)
Pimoroni BreakoutGarden: MLX90640 Thermal Camera

Architecture

Build

bin/pulsar-admin topics create persistent://public/default/garden3bin/pulsar-client consume "persistent://public/default/garden3" -s "garden3reader" -n 0class Garden(Record): cpu = Float() diskusage = String() endtime = String() equivalentco2ppm = String() host = String() hostname = String() ipaddress = String() macaddress = String() memory = Float() rowid = String() runtime = Integer() starttime = String() systemtime = String() totalvocppb = String() ts = Integer() uuid = String()----- got message -----key:[garden3_uuid_yvs_20220306191528], properties:[], content:{ "cpu": 0.0, "diskusage": "103496.6 MB", "endtime": "1646594128.2460103", "equivalentco2ppm": " 413", "host": "garden3", "hostname": "garden3", "ipaddress": "192.168.1.198", "macaddress": "dc:a6:32:32:98:20", "memory": 9.2, "rowid": "20220306191528_707b34d4-7299-4233-a495-d2d97393e834", "runtime": 0, "starttime": "03/06/2022 14:15:28", "systemtime": "03/06/2022 14:15:29", "totalvocppb": " 5", "ts": 1646594129, "uuid": "garden3_uuid_yvs_20220306191528"}presto> select * from pulsar."public/default"."garden3"; cpu | diskusage | endtime | equivalentco2ppm | host | hostname | ipaddress | macaddress | memory | rowid | runtime | -----+-------------+--------------------+------------------+---------+----------+---------------+-------------------+--------+-----------------------------------------------------+---------+------ 6.5 | 103496.5 MB | 1646594650.7116666 | 418 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192410_197b6b0c-b86c-4191-9e9c-11777767825e | 0 | 03/06 6.7 | 103496.5 MB | 1646594651.7441382 | 418 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192411_4dab3212-423b-46a9-ae39-b10eb363336d | 0 | 03/06 1.3 | 103496.5 MB | 1646594652.7764313 | 421 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192412_d24a819b-4ca1-489a-9683-da48bc37185c | 0 | 03/06 0.2 | 103496.5 MB | 1646594653.810233 | 421 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192413_f4e43177-2486-4a36-b27a-903028d6aacf | 0 | 03/06 0.0 | 103496.5 MB | 1646594654.8467774 | 416 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192414_558d3db8-725a-46ec-ad1f-89f8067142f8 | 0 | 03/06 0.0 | 103496.5 MB | 1646594655.880628 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192415_1eeea533-7f7e-4945-a089-d4b2f8681e14 | 0 | 03/06 0.0 | 103496.5 MB | 1646594656.9145741 | 418 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192416_d7d8c6ea-2adf-4704-8f49-3108a7328f26 | 0 | 03/06 0.0 | 103496.5 MB | 1646594657.9489982 | 425 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192417_c71cbb6e-c59f-4855-84ae-b796fd3d7a76 | 0 | 03/06 0.0 | 103496.5 MB | 1646594658.9828157 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192418_c14204dd-4c1c-4e76-a272-8ddecd11a97c | 0 | 03/06 0.0 | 103496.5 MB | 1646594660.0187812 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192419_c7583063-06e0-4601-806a-96619b6bb136 | 0 | 03/06 0.0 | 103496.5 MB | 1646594661.0531507 | 428 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192421_57e4a8ed-af6f-4dd0-b143-f29f1a211fdb | 0 | 03/06 0.0 | 103496.5 MB | 1646594662.087301 | 421 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192422_cf2ce36e-c996-41ac-baec-db292cffdd37 | 0 | 03/06 6.2 | 103496.5 MB | 1646594663.1214898 | 415 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192423_30b13428-ac2e-4929-b9f5-c4c3fbc3312a | 0 | 03/06 6.5 | 103496.5 MB | 1646594664.1541135 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192424_d1517315-85fa-4923-b634-9b673c5b20ba | 0 | 03/06 3.6 | 103496.5 MB | 1646594665.1890867 | 417 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192425_3984b0bc-a92e-4458-834c-e65259bb7a4d | 0 | 03/06 0.0 | 103496.5 MB | 1646594666.221572 | 422 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192426_e0debd83-47e8-43f7-8ec5-cf0dbc27b87e | 0 | 03/06 0.0 | 103496.5 MB | 1646594667.2555919 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192427_6ec920e7-56d2-4730-bddc-e18592cf1210 | 0 | 03/06 0.0 | 103496.5 MB | 1646594668.2893167 | 428 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192428_434b4458-6f89-4161-b967-f29796d8bf5d | 0 | 03/06 0.0 | 103496.5 MB | 1646594669.3234618 | 426 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192429_5bb29c2e-d078-405d-b8f6-967ea4753b3f | 0 | 03/06 0.0 | 103496.5 MB | 1646594670.359024 | 421 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192430_05b86f6b-4d28-497c-acd6-d14f7ce27157 | 0 | 03/06 0.0 | 103496.5 MB | 1646594671.392967 | 432 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192431_b7a2955a-6f39-4439-8eb9-27d7a2633836 | 0 | 03/06 0.0 | 103496.5 MB | 1646594672.4271743 | 426 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192432_29861384-fc30-4deb-bc1d-b7f2d27ef89d | 0 | 03/06 0.0 | 103496.5 MB | 1646594673.4611707 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192433_25435335-39fe-4294-b913-95c63537a743 | 0 | 03/06 0.0 | 103496.5 MB | 1646594674.4951062 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192434_a52a90e8-b11c-467b-b87f-936432bc8988 | 0 | 03/06 3.3 | 103496.5 MB | 1646594675.531778 | 436 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192435_48bab6a9-9f2e-443b-9fed-f096f6c24ebd | 0 | 03/06 6.5 | 103496.5 MB | 1646594676.5642908 | 433 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192436_761f79dc-06f6-4ed3-8062-5227b6842b77 | 0 | 03/06 6.2 | 103496.5 MB | 1646594677.5965276 | 421 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192437_6d8d49c9-0519-4825-b6b7-ed435e9fe747 | 0 | 03/06 0.0 | 103496.5 MB | 1646594678.6290672 | 423 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192438_a920872d-f152-4b18-94a7-b4dfe5641482 | 0 | 03/06 0.0 | 103496.5 MB | 1646594679.6629703 | 418 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192439_032ce574-10f6-4b50-b5e8-102b466af65a | 0 | 03/06 0.0 | 103496.5 MB | 1646594680.699419 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192440_cde6f78a-d028-4f87-a95b-156bac0ee0c2 | 0 | 03/06 0.0 | 103496.5 MB | 1646594681.7338123 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192441_7400689a-6974-4ff2-a688-96c317d45d03 | 0 | 03/06 0.0 | 103496.5 MB | 1646594682.767776 | 417 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192442_46696fa7-295c-4fe6-bf49-8d8405e21cf5 | 0 | 03/06 0.0 | 103496.5 MB | 1646594683.8017883 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192443_4de9f79c-0169-49d6-b337-fb57dcb5cf7e | 0 | 03/06 0.0 | 103496.5 MB | 1646594684.8360054 | 422 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192444_63081ac4-2c87-462d-bc16-ab506e9c6db2 | 0 | 03/06 0.0 | 103496.5 MB | 1646594685.8720167 | 420 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192445_fee13e36-26c6-4f06-894c-8b96cb0f3bae | 0 | 03/06 0.0 | 103496.5 MB | 1646594686.90594 | 431 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192446_8aaa423d-bfe3-43e8-8653-d554c2afb8d6 | 0 | 03/06 0.8 | 103496.4 MB | 1646594687.939747 | 416 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192447_bfe339cd-3fb4-4d2a-b612-3a2363e1b83b | 0 | 03/06 6.5 | 103496.4 MB | 1646594688.9728699 | 424 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192448_8809fc3e-75f8-4aca-a141-6e5d4872b0de | 0 | 03/06 6.5 | 103496.4 MB | 1646594690.0051649 | 412 | garden3 | garden3 | 192.168.1.198 | dc:a6:32:32:98:20 | 9.2 | 20220306192449_0d0b4b62-0321-4bcd-952b-14607333d9f5 | 0 | 03/06presto> desc pulsar."public/default"."garden3"; Column | Type | Extra | Comment -------------------+-----------+-------+----------------------------------------------------------------------------- cpu | real | | ["null","float"] diskusage | varchar | | ["null","string"] endtime | varchar | | ["null","string"] equivalentco2ppm | varchar | | ["null","string"] host | varchar | | ["null","string"] hostname | varchar | | ["null","string"] ipaddress | varchar | | ["null","string"] macaddress | varchar | | ["null","string"] memory | real | | ["null","float"] rowid | varchar | | ["null","string"] runtime | integer | | ["null","int"] starttime | varchar | | ["null","string"] systemtime | varchar | | ["null","string"] totalvocppb | varchar | | ["null","string"] ts | integer | | ["null","int"] uuid | varchar | | ["null","string"] __partition__ | integer | | The partition number which the message belongs to __event_time__ | timestamp | | Application defined timestamp in milliseconds of when the event occurred __publish_time__ | timestamp | | The timestamp in milliseconds of when event as published __message_id__ | varchar | | The message ID of the message used to generate this row __sequence_id__ | bigint | | The sequence ID of the message used to generate this row __producer_name__ | varchar | | The name of the producer that publish the message used to generate this row __key__ | varchar | | The partition key for the topic __properties__ | varchar | | User defined properties

Presto/Trino gives us access to all that tasty meta data for each message/event/row/record/thing/data stuff. All with special names to help prevent collisions.

Meta Data

partition - if we have a partitioned topic, which partition does this message belong to.
event_time - you know what time it is! Timestamp in ms for event action.
publish_time - when was this message published to the topic?
message_id - unique id for this message
sequence_id - ordering information for this message
producer_name - who sent me this?
key - did you assign a key like I asked you to?
properties - all those extra fields you added around the payload

Spark Structured Streaming

https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#output-sinks

val dfPulsar = spark.readStream.format("pulsar").option("service.url", "pulsar://localhost:6650").option("admin.url", "http://localhost:8080").option("topic", "persistent://public/default/garden3").load()dfPulsar.printSchema()val pQuery = dfPulsar.selectExpr("*").writeStream.format("parquet").option("truncate", false) .option("checkpointLocation", "/tmp/checkpoint").option("path", "/opt/demo/gasthermal").start() pQuery.explain()pQuery.awaitTermination()pQuery.stop()// can be "orc", "json", "csv", etc.

Show Me The Data

We can visualize data from Apache Pulsar by consuming it through the web sockets interface in a simple JQuery Single Page Web Application like below.

Example Parquet Files

pip3 install parquet-tools -Uparquet-tools inspect part-00000-b7e1f8dc-956d-4130-bc59-7b1435e41391-c000.snappy.parquet############ file meta data ############created_by: parquet-mr version 1.12.1 (build 2a5c06c58fa987f85aa22170be14d927d5ff6e7d)num_columns: 23num_rows: 1num_row_groups: 1format_version: 1.0serialized_size: 5071############ Columns ############cpudiskusageendtimeequivalentco2ppmhosthostnameipaddressmacaddressmemoryrowidruntimestarttimesystemtimetotalvocppbtsuuid __key__ topic __messageId__ publishTime__eventTimekeyvalue############ Column(cpu) ############name: cpupath: cpumax_definition_level: 1max_repetition_level: 0physical_type: FLOATlogical_type: Noneconverted_type (legacy): NONE############ Column(diskusage) ############name: diskusagepath: diskusagemax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(endtime) ############name: endtimepath: endtimemax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(equivalentco2ppm) ############name: equivalentco2ppmpath: equivalentco2ppmmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(host) ############name: hostpath: hostmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(hostname) ############name: hostnamepath: hostnamemax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(ipaddress) ############name: ipaddresspath: ipaddressmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(macaddress) ############name: macaddresspath: macaddressmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(memory) ############name: memorypath: memorymax_definition_level: 1max_repetition_level: 0physical_type: FLOATlogical_type: Noneconverted_type (legacy): NONE############ Column(rowid) ############name: rowidpath: rowidmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(runtime) ############name: runtimepath: runtimemax_definition_level: 1max_repetition_level: 0physical_type: INT32logical_type: Noneconverted_type (legacy): NONE############ Column(starttime) ############name: starttimepath: starttimemax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(systemtime) ############name: systemtimepath: systemtimemax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(totalvocppb) ############name: totalvocppbpath: totalvocppbmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(ts) ############name: tspath: tsmax_definition_level: 1max_repetition_level: 0physical_type: INT32logical_type: Noneconverted_type (legacy): NONE############ Column(uuid) ############name: uuidpath: uuidmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(__key) ############name: __keypath:__ keymax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Noneconverted_type (legacy): NONE############ Column(__topic) ############name:__topicpath: __topicmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(__messageId) ############name: __messageIdpath:__ messageIdmax_definition_level: 1max_repetition_level: 0physical_type: BYTE_ARRAYlogical_type: Noneconverted_type (legacy): NONE############ Column(__publishTime) ############name:__publishTimepath: __publishTimemax_definition_level: 1max_repetition_level: 0physical_type: INT96logical_type: Noneconverted_type (legacy): NONE############ Column(__eventTime) ############name: __eventTimepath:__ eventTimemax_definition_level: 1max_repetition_level: 0physical_type: INT96logical_type: Noneconverted_type (legacy): NONE############ Column(key) ############name: keypath: __messageProperties.key_value.keymax_definition_level: 2max_repetition_level: 1physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8############ Column(value) ############name: valuepath:__messageProperties.key_value.valuemax_definition_level: 3max_repetition_level: 1physical_type: BYTE_ARRAYlogical_type: Stringconverted_type (legacy): UTF8

Flink

CREATE CATALOG pulsar WITH ( 'type' = 'pulsar', 'service-url' = 'pulsar://pulsar1:6650', 'admin-url' = 'http://pulsar1:8080', 'format' = 'json');USE CATALOG pulsar;SHOW TABLES;Flink SQL> describe garden3;+------------------+--------+------+-----+--------+-----------+| name | type | null | key | extras | watermark |+------------------+--------+------+-----+--------+-----------+| cpu | FLOAT | true | | | || diskusage | STRING | true | | | || endtime | STRING | true | | | || equivalentco2ppm | STRING | true | | | || host | STRING | true | | | || hostname | STRING | true | | | || ipaddress | STRING | true | | | || macaddress | STRING | true | | | || memory | FLOAT | true | | | || rowid | STRING | true | | | || runtime | INT | true | | | || starttime | STRING | true | | | || systemtime | STRING | true | | | || totalvocppb | STRING | true | | | || ts | INT | true | | | || uuid | STRING | true | | | |+------------------+--------+------+-----+--------+-----------+16 rows in setselect equivalentco2ppm, totalvocppb, cpu, starttime, systemtime, ts, cpu, diskusage, endtime, memory, uuid from garden3;select max(equivalentco2ppm) as MaxCO2, max(totalvocppb) as MaxVocPPB from garden3;// TODOAdd your own table publishTime TIMESTAMP(3) METADATA, WATERMARK FOR publishTime AS publishTime - INTERVAL '5' SECOND

Apache NiFi (FLiPN)

Choose a processor from the palette

Consume messages from Apache Pulsar

Full Apache NiFi Data Flow with Apache Pulsar and MongoDB

MongoDB

mongo -u username1 -p password1 --authenticationDatabase admin pulsar1:27017/inventoryshow databasesdb.createCollection("garden3")show collectionsdb.garden3.find().pretty(){ "_id" : ObjectId("622f7315f99b9a338d60592f"), "cpu" : 0, "diskusage" : "101615.9 MB", "endtime" : "1647276083.2033532", "equivalentco2ppm" : " 407", "host" : "garden3", "hostname" : "garden3", "ipaddress" : "192.168.1.199", "macaddress" : "dc:a6:32:32:98:20", "memory" : 8.8, "rowid" : "20220314164123_0e19c5e6-45f5-405e-bd93-9aed05b37630", "runtime" : 0, "starttime" : "03/14/2022 12:41:23", "systemtime" : "03/14/2022 12:41:24", "totalvocppb" : " 5", "ts" : 1647276084, "uuid" : "garden3_uuid_xrl_20220314164123"}

References

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This content originally appeared on DEV Community and was authored by 🇺🇦Timothy Spann🇺🇦

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APA

🇺🇦Timothy Spann🇺🇦 | Sciencx (2022-04-27T22:49:00+00:00) FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest. Retrieved from https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/

MLA

" » FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest." 🇺🇦Timothy Spann🇺🇦 | Sciencx - Wednesday April 27, 2022, https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/

HARVARD

🇺🇦Timothy Spann🇺🇦 | Sciencx Wednesday April 27, 2022 » FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest., viewed ,<https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/>

VANCOUVER

🇺🇦Timothy Spann🇺🇦 | Sciencx - » FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest. [Internet]. [Accessed ]. Available from: https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/

CHICAGO

" » FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest." 🇺🇦Timothy Spann🇺🇦 | Sciencx - Accessed . https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/

IEEE

" » FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest." 🇺🇦Timothy Spann🇺🇦 | Sciencx [Online]. Available: https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/. [Accessed: ]

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» FLiP-Py-Pi-GasThermal: Building an IoT Edge Application with Apache Pulsar and Python for TVOC and CO2 Ingest | 🇺🇦Timothy Spann🇺🇦 | Sciencx | https://www.scien.cx/2022/04/27/flip-py-pi-gasthermal-building-an-iot-edge-application-with-apache-pulsar-and-python-for-tvoc-and-co2-ingest/ |

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