Main

related bits

0

processing priority

3

site type

0 (generic, awaiting analysis)

review version

11

html import

20 (imported)

Events

first seen date

2024-10-27 15:38:44

expired found date

-

created at

2024-10-27 15:38:44

updated at

2026-02-26 04:14:43

Domain name statistics

length

18

crc

18721

tld

86

nm parts

0

nm random digits

0

nm rare letters

0

Connections

is subdomain of id

87719371 (github.io)

previous id

0

replaced with id

0

related id

-

dns primary id

0

dns alternative id

0

lifecycle status

0 (unclassified, or currently active)

Subdomains and pages

deleted subdomains

0

page imported products

0

page imported random

0

page imported parking

0

Error counters

count skipped due to recent timeouts on the same server IP

0

count content received but rejected due to 11-799

0

count dns errors

0

count cert errors

0

count timeouts

0

count http 429

0

count http 404

0

count http 403

0

count http 5xx

0

next operation date

-

Server

server bits

server ip

-

Mainpage statistics

mp import status

20

mp rejected date

-

mp saved date

-

mp size orig

7762

mp size raw text

4106

mp inner links count

8

mp inner links status

20 (imported)

Open Graph

title

description

SenSys-ML is ACM Workshop on Machine Learning on Edge in Sensor Systems in conjunction with CPS-IoT Week 2024.

image

site name

author

updated

2026-02-19 08:58:28

raw text

SenSys-ML 2024 SenSys-ML 2024 13 May 2024, Hong Kong About Program Organization 2020 2019 SenSys-ML 2024 In conjunction with CPS-IoT Week 2024 The 3rd Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML 2024) Sensors have become more ubiquitous through the spread of the Internet of Things and increased market penetration of smartphones. The ensuing flood of data has the promise to advance state of the art in ways that could change the life of every human on the planet, including improvements in healthcare, environmental management, and city management. To enable this revolution machine learning needs to fill the gap to turn raw data into an understandable and actionable system. However, resource constraints, complex architectures, and challenging study designs and ground truth collection are some of the many hurdles that must be overcome to bring a promising idea to reality in this domain. ...

Text analysis

redirect type

0 (-)

block type

0 (no issues)

detected language

1 (English)

category id

Zastosowania AI (149)

index version

1

spam phrases

0

Text statistics

text nonlatin

0

text cyrillic

0

text characters

3193

text words

604

text unique words

309

text lines

62

text sentences

24

text paragraphs

5

text words per sentence

25

text matched phrases

0

text matched dictionaries

0

RSS

rss path

rss status

1 (priority 1 already searched, no matches found)

rss found date

-

rss size orig

0

rss items

0

rss spam phrases

0

rss detected language

0 (awaiting analysis)

inbefore feed id

-

inbefore status

0 (new)

Sitemap

sitemap path

sitemap status

1 (priority 1 already searched, no matches found)

sitemap review version

2

sitemap urls count

0

sitemap urls adult

0

sitemap filtered products

0

sitemap filtered videos

0

sitemap found date

-

sitemap process date

-

sitemap first import date

-

sitemap last import date

-