IoT & Edge Computing with TuskLang Python SDK

Overview

TuskLang's Python SDK provides revolutionary IoT and edge computing capabilities that enable seamless device management, real-time data processing, and intelligent edge applications. From basic sensor data collection to advanced edge AI, TuskLang makes IoT development accessible, powerful, and production-ready.

Installation & Setup

Core IoT Dependencies

Install TuskLang Python SDK with IoT extensions
pip install tuskiot[full]
Or install specific IoT components
pip install tuskiot[raspberry]  # Raspberry Pi integration
pip install tuskiot[arduino]    # Arduino integration
pip install tuskiot[sensors]    # Sensor libraries
pip install tuskiot[edge]       # Edge computing

Environment Configuration

peanu.tsk configuration for IoT workloads
iot_config = {
    "devices": {
        "raspberry_pi": {
            "enabled": true,
            "gpio_pins": [17, 18, 27, 22],
            "i2c_addresses": ["0x48", "0x76"]
        },
        "arduino": {
            "enabled": true,
            "serial_port": "/dev/ttyUSB0",
            "baud_rate": 9600
        }
    },
    "edge_computing": {
        "enabled": true,
        "local_processing": true,
        "cloud_sync": true,
        "offline_mode": true
    },
    "fujsen_integration": {
        "enable_intelligence": true,
        "real_time_processing": true,
        "predictive_analytics": true
    }
}

Basic IoT Operations

Device Management

from tuskiot import DeviceManager, SensorManager
from tuskiot.fujsen import @register_device, @discover_devices
Device manager
device_manager = DeviceManager()
@device = device_manager.register_device(
    device_id="sensor_001",
    device_type="temperature_sensor",
    location="room_101",
    capabilities=["temperature", "humidity"]
)
FUJSEN device registration
@registered_device = @register_device(
    device_id="edge_device_001",
    device_type="raspberry_pi",
    location="factory_floor",
    capabilities=["sensors", "processing", "communication"]
)
Device discovery
@discovered_devices = @discover_devices(
    network="local",
    device_types=["sensor", "actuator", "gateway"],
    timeout=30
)
Sensor management
sensor_manager = SensorManager()
@sensors = sensor_manager.get_sensors("@device")

Data Collection & Processing

from tuskiot.data import DataCollector, DataProcessor
from tuskiot.fujsen import @collect_data, @process_sensor_data
Data collection
collector = DataCollector(
    device="@device",
    sampling_rate=1.0,  # Hz
    buffer_size=1000
)
@raw_data = collector.collect_data()
FUJSEN data collection
@sensor_data = @collect_data(
    device="@device",
    sensors=["temperature", "humidity", "pressure"],
    duration=3600,  # 1 hour
    interval=1.0
)
Data processing
processor = DataProcessor()
@processed_data = processor.process(
    data="@raw_data",
    operations=["filter", "normalize", "aggregate"]
)
FUJSEN data processing
@processed_sensor_data = @process_sensor_data(
    data="@sensor_data",
    operations=["outlier_detection", "smoothing", "feature_extraction"],
    real_time=True
)

Edge Computing Features

Local Processing & Analytics

from tuskiot.edge import EdgeProcessor, LocalAnalytics
from tuskiot.fujsen import @edge_process, @local_analytics
Edge processor
edge_processor = EdgeProcessor(
    device="@device",
    processing_power="medium",
    memory_limit="512MB"
)
@edge_result = edge_processor.process(
    data="@raw_data",
    algorithms=["anomaly_detection", "prediction", "classification"]
)
FUJSEN edge processing
@edge_processing = @edge_process(
    data="@sensor_data",
    algorithms=["ml_inference", "data_compression", "feature_extraction"],
    device="@device"
)
Local analytics
analytics = LocalAnalytics()
@local_insights = analytics.analyze(
    data="@processed_data",
    metrics=["trends", "anomalies", "correlations"]
)
FUJSEN local analytics
@local_analysis = @local_analytics(
    data="@processed_data",
    analysis_types=["trend_analysis", "anomaly_detection", "predictive_modeling"],
    real_time=True
)

Edge AI & Machine Learning

from tuskiot.ai import EdgeAI, ModelManager
from tuskiot.fujsen import @edge_ai_inference, @train_edge_model
Edge AI
edge_ai = EdgeAI(
    device="@device",
    model_type="tensorflow_lite",
    optimization="quantization"
)
@ai_result = edge_ai.inference(
    data="@processed_data",
    model="@trained_model"
)
FUJSEN edge AI inference
@edge_inference = @edge_ai_inference(
    data="@sensor_data",
    model="@ml_model",
    device="@device",
    real_time=True
)
Model management
model_manager = ModelManager()
@edge_model = model_manager.deploy_model(
    model="@trained_model",
    device="@device",
    optimization="edge_optimized"
)
FUJSEN edge model training
@edge_training = @train_edge_model(
    data="@local_data",
    model_type="regression",
    target="temperature_prediction",
    device="@device"
)

Advanced IoT Features

Real-time Monitoring & Alerts

from tuskiot.monitoring import DeviceMonitor, AlertManager
from tuskiot.fujsen import @monitor_device, @send_alert
Device monitoring
monitor = DeviceMonitor(
    device="@device",
    metrics=["temperature", "humidity", "battery", "signal_strength"]
)
@monitoring_data = monitor.start_monitoring()
FUJSEN device monitoring
@device_monitor = @monitor_device(
    device="@device",
    metrics=["temperature", "humidity", "pressure"],
    threshold_alerts=True,
    real_time=True
)
Alert management
alert_manager = AlertManager()
@alert = alert_manager.create_alert(
    condition="temperature > 30",
    action="send_notification",
    priority="high"
)
FUJSEN alert sending
@alert_sent = @send_alert(
    device="@device",
    alert_type="temperature_high",
    message="Temperature exceeded threshold",
    priority="high"
)

Device Communication & Networking

from tuskiot.communication import DeviceCommunication, NetworkManager
from tuskiot.fujsen import @send_command, @receive_data
Device communication
communication = DeviceCommunication(
    protocol="mqtt",
    broker="localhost",
    port=1883
)
@connection = communication.connect("@device")
FUJSEN command sending
@command_sent = @send_command(
    device="@device",
    command="set_temperature_threshold",
    parameters={"threshold": 25.0}
)
Data reception
@received_data = @receive_data(
    device="@device",
    data_types=["sensor_data", "status_updates"],
    real_time=True
)
Network management
network_manager = NetworkManager()
@network_status = network_manager.get_network_status("@device")

IoT Data Pipelines

End-to-End IoT Pipeline

from tuskiot.pipeline import IoTPipeline
from tuskiot.fujsen import @process_iot_pipeline
Complete IoT pipeline
pipeline = IoTPipeline([
    "device_discovery",
    "data_collection",
    "edge_processing",
    "local_analytics",
    "cloud_sync",
    "alert_generation"
])
Execute pipeline
@pipeline_result = pipeline.execute(
    config={
        "devices": "@discovered_devices",
        "processing": "edge",
        "analytics": "real_time",
        "sync": "cloud"
    }
)
FUJSEN IoT pipeline
@iot_result = @process_iot_pipeline(
    devices="@discovered_devices",
    pipeline="comprehensive",
    include_analytics=True
)

Data Synchronization

from tuskiot.sync import DataSynchronizer, CloudSync
from tuskiot.fujsen import @sync_data, @backup_device_data
Data synchronization
synchronizer = DataSynchronizer(
    local_storage="@device",
    cloud_storage="tuskdb",
    sync_interval=300  # 5 minutes
)
@sync_result = synchronizer.sync_data("@processed_data")
FUJSEN data sync
@data_sync = @sync_data(
    device="@device",
    data="@processed_data",
    destination="cloud",
    compression=True
)
Cloud sync
cloud_sync = CloudSync(
    cloud_provider="tuskdb",
    bucket="iot_data",
    encryption=True
)
@cloud_backup = @backup_device_data(
    device="@device",
    data="@local_data",
    cloud_storage="tuskdb",
    retention_days=30
)

IoT Security & Privacy

Device Security

from tuskiot.security import DeviceSecurity, EncryptionManager
from tuskiot.fujsen import @secure_device, @encrypt_data
Device security
security = DeviceSecurity(
    device="@device",
    encryption="aes256",
    authentication="certificate_based"
)
@security_status = security.secure_device()
FUJSEN device security
@device_security = @secure_device(
    device="@device",
    security_level="high",
    encryption="aes256",
    authentication=True
)
Data encryption
encryption_manager = EncryptionManager()
@encrypted_data = encryption_manager.encrypt("@sensor_data")
FUJSEN data encryption
@encrypted_sensor_data = @encrypt_data(
    data="@sensor_data",
    algorithm="aes256",
    key_management="automatic"
)

Privacy Protection

from tuskiot.privacy import PrivacyManager, DataAnonymizer
from tuskiot.fujsen import @anonymize_data, @protect_privacy
Privacy management
privacy_manager = PrivacyManager()
@privacy_status = privacy_manager.protect_privacy("@device")
FUJSEN privacy protection
@privacy_protection = @protect_privacy(
    device="@device",
    data_types=["personal", "sensitive"],
    anonymization=True
)
Data anonymization
anonymizer = DataAnonymizer()
@anonymized_data = anonymizer.anonymize("@sensor_data")
FUJSEN data anonymization
@anonymized_sensor_data = @anonymize_data(
    data="@sensor_data",
    anonymization_level="high",
    preserve_utility=True
)

IoT with TuskLang Ecosystem

Integration with TuskDB

from tuskiot.storage import TuskDBStorage
from tuskiot.fujsen import @store_iot_data, @load_device_config
Store IoT data in TuskDB
@iot_storage = TuskDBStorage(
    database="iot_data",
    collection="sensor_readings"
)
@store_data = @store_iot_data(
    device="@device",
    data="@sensor_data",
    metadata={
        "timestamp": "@timestamp",
        "location": "@device.location",
        "device_type": "@device.type"
    }
)
Load device configuration
@device_config = @load_device_config(
    device_id="@device.id",
    config_type="operational"
)

IoT with FUJSEN Intelligence

from tuskiot.fujsen import @iot_intelligence, @smart_device_management
FUJSEN-powered IoT intelligence
@intelligent_analysis = @iot_intelligence(
    device="@device",
    data="@sensor_data",
    intelligence_level="advanced",
    include_predictions=True
)
Smart device management
@smart_management = @smart_device_management(
    device="@device",
    management_types=["automated", "predictive", "adaptive"],
    optimization=True
)

Best Practices

Performance Optimization

from tuskiot.optimization import DeviceOptimizer, PowerManager
from tuskiot.fujsen import @optimize_device, @manage_power
Device optimization
optimizer = DeviceOptimizer()
@optimized_device = optimizer.optimize("@device")
FUJSEN device optimization
@device_optimization = @optimize_device(
    device="@device",
    optimization_types=["power", "performance", "battery"],
    adaptive=True
)
Power management
power_manager = PowerManager()
@power_status = power_manager.manage_power("@device")
FUJSEN power management
@power_management = @manage_power(
    device="@device",
    power_mode="adaptive",
    battery_optimization=True
)

Reliability & Fault Tolerance

from tuskiot.reliability import ReliabilityManager, FaultTolerance
from tuskiot.fujsen import @ensure_reliability, @handle_faults
Reliability management
reliability_manager = ReliabilityManager()
@reliability_status = reliability_manager.ensure_reliability("@device")
FUJSEN reliability
@device_reliability = @ensure_reliability(
    device="@device",
    reliability_level="high",
    fault_tolerance=True
)
Fault tolerance
fault_tolerance = FaultTolerance()
@fault_handling = fault_tolerance.handle_faults("@device")
FUJSEN fault handling
@fault_management = @handle_faults(
    device="@device",
    fault_types=["hardware", "software", "network"],
    auto_recovery=True
)

Example: Smart Home IoT System

Complete smart home IoT system
from tuskiot import *
Discover and register devices
@home_devices = @discover_devices(
    network="home_wifi",
    device_types=["sensor", "actuator", "smart_plug"]
)
@registered_devices = @register_device(
    devices="@home_devices",
    location="home",
    capabilities=["automation", "monitoring"]
)
Set up monitoring and automation
@monitoring = @monitor_device(
    devices="@registered_devices",
    metrics=["temperature", "humidity", "motion", "power_consumption"],
    real_time=True
)
@automation = @edge_process(
    data="@monitoring",
    algorithms=["comfort_optimization", "energy_saving", "security_monitoring"],
    devices="@registered_devices"
)
Cloud sync and analytics
@cloud_sync = @sync_data(
    devices="@registered_devices",
    data="@automation",
    destination="tuskdb"
)
@analytics = @local_analytics(
    data="@automation",
    analysis_types=["energy_optimization", "comfort_analysis", "security_insights"]
)

Conclusion

TuskLang's Python SDK provides a comprehensive IoT and edge computing ecosystem that enables seamless device management, real-time data processing, and intelligent edge applications. From basic sensor data collection to advanced edge AI, TuskLang makes IoT development accessible, powerful, and production-ready.

The integration with TuskDB, FUJSEN intelligence, and the broader TuskLang ecosystem creates a unique IoT platform that scales from simple sensor networks to enterprise-grade edge computing systems. Whether you're building smart homes, industrial IoT, or autonomous systems, TuskLang provides the tools and infrastructure you need to succeed.

Embrace the future of IoT and edge computing with TuskLang - where connected devices meet revolutionary technology.